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3.1 Location probability
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Location probability is a quality criterion for cell coverage. Due to shadowing and fading a cell edge is defined by adding margins so that the minimum service quality is fulfilled with a certain probability. For car mobile traffic a usual measure is 90 % area coverage per cell, taking into account the minimum signal-to-noise ratio Ec/No under multipath fading conditions. For lognormal shadowing an area coverage can be translated into a location probability on cell edge (Jakes, 1974). For the normal case of urban propagation with a standard deviation of 7 dB and a distance exponential of 3.5, 90 % area coverage corresponds to about 75 % location probability at the cell edge. Furthermore, the lognormal shadow margin in this case will be 5 dB, as described in CEPT Recommendation T/R 25-03 and CCIR Report 740.
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3.2 Ec/No threshold
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The mobile radio channel is characterized by wideband multipath propagation effects such as delay spread and Doppler shift as defined in GSM 05.05 annex C. The reference signal-to-noise ratio in the modulating bit rate bandwidth (271 kHz) is Ec/No = 8 dB including 2 dB implementation margin for the GSM system at the minimum service quality without interference. The Ec/No quality threshold is different for various logical channels and propagation conditions as described in GSM 05.05.
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3.3 RF-budgets
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The RF-link between a Base Transceiver Station (BTS) and a Mobile Station (MS) including handheld is best described by an RF-budget as in annex A which consists of 4 such budgets; A.1 for GSM 900 MS class 4; A.2 for GSM 900 MS class 2, A.3 for DCS 1800 MS classes 1 and 2, and A.4 for GSM 900 class 4 in small cells. The antenna gain for the hand portable unit can be set to 0 dBi due to loss in the human body as described in CCIR Report 567. An explicit body loss factor is incorporated in annex A.3 At 900 MHz, the indoor loss is the field strength decrease when moving into a house on the bottom floor on 1.5 m height from the street. The indoor loss near windows ( < 1 m) is typically 12 dB. However, the building loss has been measured by the Finnish PTT to vary between 37 dB and -8 dB with an average of 18 dB taken over all floors and buildings (Kajamaa, 1985). See also CCIR Report 567. At 1800 MHz, the indoor loss for large concrete buildings was reported in COST 231 TD(90)117 and values in the range 12 - 17 dB were measured. Since these buildings are typical of urban areas a value of 15 dB is assumed in annex A.3. In rural areas the buildings tend to be smaller and a 10 dB indoor loss is assumed. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 8 (GSM 03.30 version 7.1.0 Release 1998) The isotropic power is defined as the RMS value at the terminal of an antenna with 0 dBi gain. A quarter-wave monopole mounted on a suitable earth-plane (car roof) without losses has antenna gain 2 dBi. An isotropic power of -113 dBm corresponds to a field strength of 23.5 dBuV/m for 925 MHz and 29.3 dBuV/m at 1795 MHz, see CEPT Recommendation T/R 25-03 and GSM 05.05 section 5 for formulas. GSM900 BTS can be connected to the same feeders and antennas as analog 900 MHz BTS by diplexers with less than 0.5 dB loss.
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3.4 Cell ranges
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3.4.1 Large cells
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In large cells the base station antenna is installed above the maximum height of the surrounding roof tops; the path loss is determined mainly by diffraction and scattering at roof tops in the vicinity of the mobile i.e. the main rays propagate above the roof tops; the cell radius is minimally 1 km and normally exceeds 3 km. Hata's model and its extension up to 2000 MHz (COST 231-Hata model) can be used to calculate the path loss in such cells (see COST 231 TD (90) 119 Rev 2 and annex B). The field strength on 1.5 m reference height outdoor for MS including handheld is a value which inserted in the curves of CCIR Report 567-3 Figure 2 (Okumura) together with the BTS antenna height and effective radiated power (ERP) yields the range and re-use distance for urban areas (section 5.2). The cell range can also be calculated by putting the maximum allowed path loss between isotropic antennas into the Figures 1 to 3 of annex C. The same path loss can be found in the RF-budgets in annex A. The figures 1 and 2 (GSM 900) in annex C are based on Hata's propagation model which fits Okumura's experimental curves up to 1500 MHz and figure 3 (DCS 1800) is based on COST 231-Hata model according to COST 231 TD (90) 119 Rev 2. The example RF-budget shown in annex A.1 for a GSM900 MS handheld output power 2 W yields about double the range outdoors compared with indoors. This means that if the cells are dimensioned for handhelds with indoor loss 10 dB, the outdoor coverage for MS will be interference limited, see section 4.2. Still more extreme coverage can be found over open flat land of 12 km as compared with 3 km in urban areas outdoor to the same cell site. For GSM 900 the Max EIRP of 50 W matches MS class 2 of max peak output power 8 W, see annex A.2. An example RF budget for DCS 1800 is shown in annex A.3. Range predictions are given for 1 W and 250 mW DCS 1800 MS with BTS powers which balance the up- and down- links. The propagation assumptions used in annex A1, A2, A3 are shown in the tables below : For GSM 900: Rural Rural Urban (Open Area) (Quasi-open) Base station 100 100 50 height (m) Mobile height (m) 1.5 1.5 1.5 Hata's loss 90.7+31.8log(d) 95.7+31.8log(d) 123.3+33.7log(d) formula (d in km) Indoor Loss (dB) 10 10 15 ETSI ETSI TR 101 362 V7.1.0 (2000-04) 9 (GSM 03.30 version 7.1.0 Release 1998) For DCS 1800: Rural Rural Urban (*) (Open Area) (Quasi-Open) Base station 60 60 50 height (m) Mobile height (m) 1.5 1.5 1.5 COST 231 100.1+33.3log(d) 105.1+33.3log(d) 133.2+33.8log (d) Hata's loss formula (d in km) Indoor Loss (dB) 10 10 15 (*) medium sized city and suburban centres (see COST 231 TD (90) 119 Rev2). For metropolitan centres add 3 dB to the path loss. NOTE 1: The rural (Open Area) model is useful for desert areas and the rural (Quasi-Open) for countryside. NOTE 2: The correction factors for Quasi-open and Open areas are applicable in the frequency range 100-2000 MHz (Okumura,1968).
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3.4.2 Small cells
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For small cell coverage the antenna is sited above the median but below the maximum height of the surrounding roof tops and so therefore the path loss is determined by the same mechanisms as stated in section 3.4.1. However large and small cells differ in terms of maximum range and for small cells the maximum range is typically less than 1-3 km. In the case of small cells with a radius of less than 1 km the Hata model cannot be used. The COST 231-Walfish-Ikegami model (see annex B) gives the best approximation to the path loss experienced when small cells with a radius of less than 5 km are implemented in urban environments. It can therefore be used to estimate the BTS ERP required in order to provide a particular cell radius (typically in the range 200 m - 3 km). The cell radius can be calculated by putting the maximum allowed path loss between the isotropic antennas into figure 4 of annex C. The following parameters have been used to derive figure 4: Width of the road, w = 20 m Height of building roof tops, Hroof = 15 m Height of base station antenna, Hb = 17 m Height of mobile station antenna, Hm = 1.5 m Road orientation to direct radio path, Phi = 90° Building separation, b = 40 m For GSM 900 the corresponding propagation loss is given by : Loss (dB) = 132.8 + 38log(d/km) For DCS 1800 the corresponding propagation loss is given by : Loss (dB) = 142,9 + 38log(d/km) for medium sized cities and suburban centres Loss (dB) = 145,3 + 38log(d/km) for metropolitan centres An example of RF budget for a GSM 900 Class 4 MS in a small cell is shown in annex A.4. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 10 (GSM 03.30 version 7.1.0 Release 1998)
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3.4.3 Microcells
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COST 231 defines a microcell as being a cell in which the base station antenna is mounted generally below roof top level. Wave propagation is determined by diffraction and scattering around buildings i.e. the main rays propagate in street canyons. COST 231 proposes the following experimental model for microcell propagation when a free line of sight exists in a street canyon : Path loss in dB (GSM 900) = 101,7 + 26log(d/km) d > 20 m Path loss in dB (DCS 1800) = 107,7 + 26log(d/km) d > 20 m The propagation loss in microcells increases sharply as the receiver moves out of line of sight, for example, around a street corner. This can be taken into account by adding 20 dB to the propagation loss per corner, up to two or three corners (the propagation being more of a guided type in this case). Beyond, the complete COST231-Walfish-Ikegami model as presented in annex B should be used. Microcells have a radius in the region of 200 to 300 metres and therefore exhibit different usage patterns from large and small cells. They can be supported by generally smaller and cheaper BTS's. Since there will be many different microcell environments, a number of microcell BTS classes are defined in GSM 05.05. This allows the most appropriate microcell BTS to be chosen based upon the Minimum Coupling Loss expected between MS and the microcell BTS. The MCL dictates the close proximity working in a microcell environment and depends on the relative BTS/MS antenna heights, gains and the positioning of the BTS antenna. In order to aid cell planning, the micro-BTS class for a particular installation should be chosen by matching the measured or predicted MCL at the chosen site with the following table. The microcell specifications have been based on a frequency spacing of 6 MHz between the microcell channels and the channels used by any other cell in the vicinity. However, for smaller frequency spacings (down to 1.8 MHz) a larger MCL must be maintained in order to guarantee successful close proximity operation. This is due to an increase in wideband noise and a decrease in the MS blocking requirement from mobiles closer to the carrier. Micro-BTS class Recommended MCL (GSM 900) Recommended MCL (DCS 1800) Normal Small freq. spacing Normal Small freq. spacing M1 60 64 60 68 M2 55 59 55 63 M3 50 54 50 58 Operators should note that when using the smaller frequency spacing and hence larger MCL the blocking and wideband noise performance of the micro-BTS will be better than necessary. Operators should exercise caution in choosing the microcell BTS class and transmit power. If they depart from the recommended parameters in 05.05 they risk compromising the performance of the networks operating in the same frequency band and same geographical area.
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4 Channel re-use
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4.1 C/Ic threshold
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The C/Ic threshold is the minimum co-channel carrier-to-interference ratio in the active part of the timeslot at the minimum service quality when interference limited. The reference threshold C/Ic = 9 dB includes 2 dB implementation margin on the simulated residual BER threshold The threshold quality varies with logical channels and propagation conditions, see GSM 05.05.
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4.2 Trade-off between Ec/No and C/Ic
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For planning large cells the service range can be noise limited as defined by Ec/No plus a degradation margin of 3 dB protected by 3 dB increase of C/Ic, see annex A. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 11 (GSM 03.30 version 7.1.0 Release 1998) For planning small cells it can be more feasible to increase Ec/No by 6 dB corresponding to an increase of C/Ic by 1 dB to cover shadowed areas better. C/(I+N) = 9 dB represents the GSM limit performance. To permit handheld coverage with 10 dB indoor loss, the Ec/No has to be increased by 10 dB outdoors corresponding to a negligible increase of C/Ic outdoors permitting about the same interference limited coverage for MS including handhelds. The range outdoors can also be noise limited like the range indoors as shown in section 3.4 and annex A.1.
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4.3 Adjacent channel suppressions
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Adjacent channel suppression (ACS) is the gain (Ia/Ic) in C/I when wanted and unwanted GSM RF-signals co-exist on adjacent RF channels whilst maintaining the same quality as in the co-channel case, i.e. ACS = C/Ic - C/Ia. Taking into account frequency errors and fading conditions in the product of spectrum and filter of wanted and unwanted GSM RF-signals, ACS = 18 dB is typical as can be found in GSM 05.05. 1st ACS >= 18 dB, i.e. C/Ia1 <= -9 dB for C/Ic = 9 dB in GSM 05.05, imposes constraints of excluding the 1st adjacent channel in the same cell. However, the 1st adjacent channel can be used in the 1st adjacent cell, as C/Ic <= 12 dB and ACS >= 18 dB gives an acceptable handover- margin of >= 6 dB for signalling back to the old BTS as shown in GSM 05.08. An exception might be adjacent cells using the same site due to uplink interference risks. 2nd ACS >= 50 dB, i.e. C/Ia2 <= -41 dB for C/Ic = 9 dB in GSM 05.05, implies that due to MS power control in the uplink, as well as intra-cell handover, it is possible that the 2nd adjacent channel can be used in the same cell. Switching transients are not interfering due to synchronized transmission and reception of bursts at co-located BTS.
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4.4 Antenna patterns
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Antenna patterns including surrounding masts, buildings, and terrain measured on ca 1 km distance will always look directional, even if the original antenna was non-directional. In order to achieve a front-to-back ratio F/B of greater than 20 dB from an antenna with an ideal F/B > 25 dB, backscattering from the main lobe must be suppressed by using an antenna height of at least 10 m above forward obstacles in ca 0.5 km. In order to achieve an omni-directional pattern with as few nulls as possible, the ideal non-directional antenna must be isolated from the mast by a suitable reflector. The nulls from mast scattering are usually in different angles for the duplex frequencies and should be avoided because of creating path loss imbalance. The main lobe antenna gains are typically 12-18 dBi for BTS, and 2-5 dBi for MS. Note that a dipole has the gain 0 dBd = 2 dBi.
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4.5 Antenna heights
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The height gain under Rayleigh fading conditions is approximately 6 dB by doubling the BTS antenna height. The same height gain for MS and handheld from reference height 1.5 m to 10 m is about 9 dB, which is the correction needed for using CCIR Recommendation 370.
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4.6 Path loss balance
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Path loss balance on uplink and downlink is important for two-way communication near the cell edge. Speech as well as data transmission is dimensioned for equal quality in both directions. Balance is only achieved for a certain power class (section 3.4). Path loss imbalance is taken care of in cell selection in idle mode and in the handover decision algorithms as found in GSM 05.08. However, a cell dimensioned for 8 W MS (GSM 900 class 2) can more or less gain balance for 2 W MS handheld (GSM 900 class 4) by implementing antenna diversity reception on the BTS.
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4.7 Cell dimensioning
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Cell dimensioning for uniform traffic distribution is optimized by at any time using the same number of channels and the same coverage area per cell. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 12 (GSM 03.30 version 7.1.0 Release 1998) Cell dimensioning for non-uniform traffic distribution is optimized by at any time using the same number of channels but changing the cell coverage area so that the traffic carried per cell is kept constant with the traffic density. Keeping the path loss balance by directional antennas pointing outwards from the traffic peaks the effective radiated power (ERP) per BTS can be increased rapidly out-wards. In order to make the inner cells really small the height gain can be decreased and the antenna gain can be made smaller or even negative in dB by increasing the feeder loss but keeping the antenna front-to-back ratio constant (section 4.4).
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4.8 Channel allocation
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Channel allocation is normally made on an FDMA basis. However, in synchronized networks channel allocation can be made on a TDMA basis. Note that a BCCH RF channel must always be fully allocated to one cell. Channel allocation for uniform traffic distribution preferably follows one of the well known re-use clusters depending on C/I-distribution, e.g. a 9-cell cluster (3-cell 3-site repeat pattern) using 9 RF channel groups or cell allocations (CAs), (Stjernvall, 1985). Channel allocation for non-uniform traffic distribution preferably follows a vortex from a BTS concentration on the traffic centre, if a bell-shaped area traffic model holds. In real life the traffic distribution is more complicated with also line and point traffic. In this case the cell areas will be rather different for various BTS locations from city centre. The channel allocation can be optimized by using graph colouring heuristics as described in CCIR Report 842. Base transceiver station identity code (BSIC) allocation is done so that maximum re-use distance per carrier is achieved in order to exclude co-channel ambiguity. Frequency co-ordination between countries is a matter of negotiations between countries as described in CEPT Recommendation T/R 25-04. Co-channel and 200 kHz adjacent channels need to be considered between PLMNs and other services as stated in GSM 05.05. Frequency sharing between GSM countries is regulated in CEPT Recommendation T/R 20-08 concerning frequency planning and frequency co-ordination for the GSM service.
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4.9 Frequency hopping
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Frequency hopping (FH) can easily be implemented if the re-use is based on RF channel groups (CAs). It is also possible to change allocation by demand as described in GSM 05.02. In synchronized networks the synchronization bursts (SB) on the BCCH will occur at the same time on different BTS. This will increase the time to decode the BSIC of adjacent BTS, see GSM 05.08. The SACCH on the TCH or SDCCH will also occur at the same time on different BTS. This will decrease the advantage of discontinuous transmission (DTX). In order to avoid this an offset in the time base (FN) between BTS may be used. If channel allocation is made on a TDMA basis and frequency hopping is used, the same hop sequence must be used on all BTS. Therefore the same time base and the same hopping sequence number (HSN) shall be used.
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4.10 Cells with extra long propagation delay
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Cells with anticipated traffic with ranges more than 35 km corresponding to maximum MS timing advance can work properly if the timeslot after the CCCH and the timeslot after the allocated timeslot are not used by the BTS corresponding to a maximum total range of 120 km.
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5 Propagation models
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5.1 Terrain obstacles
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Terrain obstacles introduce diffraction loss, which can be estimated from the path profile between transmitter and receiver antennas. The profile can preferably be derived from a digital topographic data bank delivered from the national map survey or from a land resource satellite system, e.g. Spot. The resolution is usually 500*500 m2 down to ETSI ETSI TR 101 362 V7.1.0 (2000-04) 13 (GSM 03.30 version 7.1.0 Release 1998) 50*50 m2 in side and 20 m down to 5 m in height. This resolution is not sufficient to describe the situation in cities for microcells, where streets and buildings must be recognized.
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5.2 Environment factors
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Environment factors for the nearest 200 m radius from the mobile play an important role in both the 900 MHz and 1800 MHz bands. For the Nordic cellular planning for NMT there is taken into account 10 categories for land, urban and wood. Further studies are done within COST 231. Coarse estimations of cell coverage can be done on pocket computers with programs adding these environment factors to propagation curves of CCIR Recommendation 370-5 figure 9 and CCIR Report 567-3 figure 2 (Okumura, 1968).
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5.3 Field strength measurements
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Field strength measurements of the local mean of the lognormal distribution are preferably done by digital averaging over the typical Rayleigh fading. It can be shown that the local average power can be estimated over 20 to 40 wavelengths with at least 36 uncorrelated samples within 1 dB error for 90 % confidence (Lee, 1985).
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5.4 Cell adjustments
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Cell adjustments from field strength measurements of coverage and re-use are recommended after coarse predictions have been done. Field strength measurements of rms values can be performed with an uncertainty of 3.5 dB due to sampling and different propagation between Rayleigh fading and line-of-sight. Predictions can reasonably be done with an uncertainty of about 10 dB. Therefore cell adjustments are preferably done from field strength measurements by changing BTS output power, ERP, and antenna pattern in direction and shape.
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6 Glossary
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ACS Adjacent Channel Suppression (section 4.3) BCCH Broadcast Control Channel (section 4.8) BTS Base Transceiver Station (section 3.3) BSIC Base Transceiver Station Identity Code (section 4.8) CA Cell Allocation of radio frequency channels (section 4.8) CCCH Common Control Channel (section 4.10) COST European Co-operation in the field of Scientific and Technical Research DTX Discontinuous Transmission (section 4.9) Ec/No Signal-to-Noise ratio in modulating bit rate bandwidth (section3.2) FH Frequency Hopping (section 4.9) FN TDMA Frame Number (section 4.9) F/B Front-to-Back ratio (section 4.4) HSN Hopping Sequence Number (section 4.9) MS Mobile Station (section 3.3) PLMN Public Land Mobile Network Ps Location (site) Probability (section 3.1) ETSI ETSI TR 101 362 V7.1.0 (2000-04) 14 (GSM 03.30 version 7.1.0 Release 1998) SACCH Slow Associated Control Channel (section 4.9) SB Synchronization Burst (section 4.9) SDCCH Stand-alone Dedicated Control Channel (section 4.9) TCH Traffic Channel (section 4.9)
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7 Bibliography
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CEPT Recommendation T/R 20-08 Frequency planning and frequency co-ordination for the GSM service; CEPT Recommendation T/R 25-03 Co-ordination of frequencies for the land mobile service in the 80, 160 and 460 MHz bands and the methods to be used for assessing interference; CEPT Recommendation T/R 25-04 Co-ordination in frontier regions of frequencies for the land mobile service in the bands between 862 and 960 MHz; CEPT Liaison office, P.O. Box 1283, CH-3001 Berne. 1 Jakes, W.C., Jr.(Ed.) (1974) Microwave mobile communications. John Wiley, New York, NY, USA. 2 Kajamaa, Timo (1985) 900 MHz propagation measurements in Finland in 1983-85 (PTT Report 27.8.1985.) Proc NRS 86, Nordic Radio Symposium, ISBN 91-7056-072-2. 3 Lee, W.C.Y. (Feb., 1985) Estimate of local average power of a mobile radio signal. IEEE Trans. Vehic. Tech., Vol. VT-34, 1. 4 Okumura, Y. et al (Sep.-Oct., 1968) Field strength and its variability in VHF and UHF land-mobile radio service. Rev. Elec. Comm. Lab., NTT, Vol. 16, 9-10. 5 Stjernvall, J-E (Feb. 1985) Calculation of capacity and co-channel interference in a cellular system. Nordic Seminar on Digital Land Mobile Radio Communication (DMR I), Espoo, Finland. 6 A.M.D. Turkmani, J.D. Parsons and A.F. de Toledo "Radio Propagation into Buildings at 1.8 GHz". COST 231 TD (90) 117 7 COST 231 "Urban transmission loss models for mobile radio in the 900- and 1800- MHz bands (Revision 2)" COST 231 TD (90) 119 Rev 2. 8 Hata, M. (1980) Empirical Formula for Propagation Loss in Land Mobile Radio Services, IEEE Trans. on Vehicular Technology VT-29. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 15 (GSM 03.30 version 7.1.0 Release 1998) Annex A.1: (class 4) Example of RF-budget for GSM MS handheld RF-output peak power 2 W Propagation over land in urban and rural areas Receiving end: BTS MS Eq. TX: MS BTS (dB) Noise figure (multicoupl.input) dB 8 10 A Multipath profile 1) TU50 TU50 (no FH) Ec/No min. fading 1) dB 8 8 B RX RF-input sensitivity dBm -104 -102 C=A+B+W-174 Interference degrad. margin dB 3 3 D RX-antenna cable type 1-5/8" 0 Specific cable loss dB/100m 2 0 Antenna cable length m 120 0 Cable loss + connector dB 4 0 E RX-antenna gain dBi 12 0 F Isotropic power, 50 % Ps dBm -109 -99 G=C+D+E-F Lognormal margin 50 % -> 75 % Ps dB 5 5 H Isotropic power, 75 % Ps dBm -104 -94 I=G+H Field strength, 75 % Ps dBuV/m 33 43 J=I+137 C/Ic min.fading, 50 % Ps 1) dB 9 9 C/Ic prot. at 3 dB degrad. dB 12 12 C/Ic protection, 75 % Ps 2) dB 19 19 Transmitting end: MS BTS Eq. RX: BTS MS (dB) TX RF-output peak power W 2 6 (mean power over burst) dBm 33 38 K Isolator + combiner + filter dB 0 3 L RF peak power, combiner output dBm 33 35 M=K-L TX-antenna cable type 0 1-5/8" Specific cable loss dB/100m 0 2 Antenna cable length m 0 120 ETSI ETSI TR 101 362 V7.1.0 (2000-04) 16 (GSM 03.30 version 7.1.0 Release 1998) Cable loss + connector dB 0 4 N TX-antenna gain dBi 0 12 O Peak EIRP W 2 20 (EIRP = ERP + 2 dB) dBm 33 43 P=M-N+O Isotropic path loss, 50 % Ps 3) dB 139 139 Q=P-G-3 Isotropic path loss, 75 % Ps dB 134 134 R=P-I-3 Range, outdoor, 75 % Ps 4) km 2.0 2.0 Range, indoor, 75 % Ps 4) km 0.7 0.7 1) Ec/No and C/Ic for residual BER = 0.4 %, TCH/FS (class Ib) and multi-path profiles as defined in GSM 05.05 annex 3. Bandwidth W = 54 dBHz. 2) Uncorrelated C and I with 75 % location probability (Ps). lognormal distribution of shadowing with standard deviation 7 dB. Ps = 75 % corresponds to ca 90 % area coverage, see Jakes, pp.126-127. 3) 3 dB of path loss is assumed to be due to the antenna/body loss 4) Max. range based on Hata. Antenna heights for BTS = 50 m and MS = 1.5 m. Indoor loss = 15 dB. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 17 (GSM 03.30 version 7.1.0 Release 1998) Annex A.2: (class 2) Example of RF-budget for GSM MS RF-output peak power 8 W Propagation over land in urban and rural areas Receiving end: BTS MS Eq. TX: MS BTS (dB) Noise figure (multicoupl.input) dB 8 8 A Multipath profile 1) RA250 RA250 (no FH) Ec/No min. fading 1) dB 8 8 B RX RF-input sensitivity dBm -104 -104 C=A+B+W-174 Interference degrad. margin dB 3 3 D RX-antenna cable type 1-5/8" RG-58 Specific cable loss dB/100m 2 50 Antenna cable length m 120 4 Cable loss + connector dB 4 2 E RX-antenna gain dBi 12 2 F Isotropic power, 50 % Ps dBm -109 -101 G=C+D+E-F Lognormal margin 50 % -> 75 % Ps dB 5 5 H Isotropic power, 75 % Ps dBm -104 -96 I=G+H Field strength, 75 % Ps dBuV/m 33 41 J=I+137 C/Ic min.fading, 50 % Ps 1) dB 9 9 C/Ic prot. at 3 dB degrad. dB 12 12 C/Ic protection, 75 % Ps 2) dB 19 19 Transmitting end: MS BTS Eq. RX: BTS MS (dB) TX RF-output peak power W 8 16 (mean power over burst) dBm 39 42 K Isolator + combiner + filter dB 0 3 L RF peak power, combiner output dBm 39 39 M=K-L TX-antenna cable type RG-58 1-5/8" Specific cable loss dB/100m 50 2 Antenna cable length m 4 120 Cable loss + connector dB 2 4 N TX-antenna gain dBi 2 12 O Peak EIRP W 20 50 (EIRP = ERP + 2 dB) dBm 39 47 P=M-N+O Isotropic path loss, 50 % Ps dB 148 148 Q=P-G Isotropic path loss, 75 % Ps dB 143 143 R=P-I Range, outdoor, 75 % Ps 3) km 30.7 30.7 1) Ec/No and C/Ic for residual BER = 0.2 %, TCH/FS (class Ib) and multi-path profiles as defined in GSM 05.05 annex 3. Bandwidth W = 54 dBHz. 2) Uncorrelated C and I with 75 % location probability (Ps). Lognormal distribution of shadowing with standard deviation 7 dB. Ps = 75 % corresponds to ca 90 % area coverage, see Jakes, pp.126-127. 3) Max. range in quasi-open areas based on Hata. Antenna heights for BTS = 100 m and MS = 1.5 m. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 18 (GSM 03.30 version 7.1.0 Release 1998) Annex A.3: (DCS1800 classes 1&2): Example of RF-budget for DCS 1800 MS RF-output peak power 1 W & 250 mW Propagation over land in urban and rural areas Receiving end: BTS MS Eq. TX: MS BTS (dB) Noise figure(multicoupl.input) dB 8 12 A Multipath profile TU50 or RA130 Ec/No min. fading dB 8 8 B RX RF-input sensitivity dBm -104 -100 C=A+B+W-174 Interference degrad. margin dB 3 3 D (W=54.3 dBHz) Cable loss + connector dB 2 0 E RX-antenna gain dBi 18 0 F Diversity gain dB 5 0 F1 Isotropic power, 50 % Ps dBm -122 -97 G=C+D+E-F-F1 Lognormal margin 50 % ->75 % Ps dB 6 6 H Isotropic power, 75 % Ps dBm -116 -91 I=G+H Field Strength 75 % Ps 27 51 J=I+142.4 at 1.8 GHz Transmitting end: MS BTS Eq. RX: BTS MS (dB) TX PA output peak power W - 15.8/3.98 (mean power over burst) dBm - 42/36 K Isolator + combiner + filter dB - 3 L RF Peak power,(ant.connector) dBm 30/24 39/33 M=K-L 1) W 1.0/0.25 7.9/2.0 Cable loss + connector dB 0 2 N TX-antenna gain dBi 0 18 O Peak EIRP W 1.0/0.25 316/79.4 dBm 30/24 55/49 P=M-N+O Isotropic path loss,50 % Ps 2) dB 149/143 149/143 Q=P-G-3 Isotropic path loss, 75 % Ps dB 143/137 143/137 R=P-I-3 Range km - 75 % Ps Urban, out of doors 1.91/1.27 Urban, indoors 0.69/0.46 Rural (Open area), out of doors 19.0/12.6 Rural (Open area), indoors 9.52/6.28 1) The MS peak power is defined as: a) If the radio has an antenna connector, it shall be measured into a 50 Ohm resistive load. b) If the radio has an integral antenna, a reference antenna with 0 dBi gain shall be assumed. 2) 3 dB of the path loss is assumed to be due to antenna/body loss. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 19 (GSM 03.30 version 7.1.0 Release 1998) Annex A.4: Example of RF-budget for GSM 900 Class4 (peak power 2 W) in a small cell Propagation over land in urban and rural areas Receiving end: BTS MS Eq. TX : MS BTS (dB) Noise figure(multicoupl.input) dB 8 10 A Multipath profile TU50 TU50 Ec/No min. fading dB 8 8 B RX RF-input sensitivity dBm -104 -102 C=A+B+W-174 Interference degrad. margin dB 3 3 D (W=54.3 dBHz) Cable loss + connector dB 2 0 E RX-antenna gain dBi 16 0 F Diversity gain dB 3 0 F1 Isotropic power, 50 % Ps dBm -118 -99 G=C+D+E-F-F1 Lognormal margin 50 % ->75 % Ps dB 5 5 H Isotropic power, 75 % Ps dBm -113 -94 I=G+H Field Strength 75 % Ps 24 43 J=I+137 at 900 MHz Transmitting end: MS BTS Eq. RX: BTS MS (dB) TX PA output peak power W - 12.6 (mean power over burst) dBm - 41 K Isolator + combiner + filter dB - 3 L RF Peak power,(ant.connector) dBm 33 38 M=K-L 1) W 2 6.3 Cable loss + connector dB 0 2 N TX-antenna gain dBi 0 16 O Peak EIRP W 2 158 dBm 33 52 P=M-N+O Isotropic path loss,50 % Ps 2) dB 148 148 Q=P-G-3 Isotropic path loss, 75 % Ps dB 143 143 R=P-I-3 Range km - 75 % Ps Urban, out of doors 1.86 Urban, indoors 0.75 1) The MS peak power is defined as: a) If the radio has an antenna connector, it shall be measured into a 50 Ohm resistive load. b) If the radio has an integral antenna, a reference antenna with 0 dBi gain shall be assumed. 2) 3 dB of the path loss is assumed to be due to antenna/body loss. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 20 (GSM 03.30 version 7.1.0 Release 1998) Annex B: Propagation loss formulas for mobile radiocommunications B.1 Hata Model [4], [8] Frequency f: 150 - 1000 MHz Base station height Hb: 30 - 200 m Mobile height Hm: 1 - 10 m Distance d: 1 - 20 km Large and small cells (i.e. base station antenna heights above roof-top levels of buildings adjacent to the base station) B.1.1 Urban Lu (dB) = 69.55 + 26.16*log(f) - 13.82*log(Hb) - a(Hm) + [44.9 - 6.55*log(Hb)]*log(d) a(Hm) correction factor for vehicular station antenna height. For a medium-small city : a (Hm) = [1.1*log(f) - 0.7]*Hm - [1.56*log(f) - 0.8] For a large city : a (Hm) = 8.29*[log(1.54*Hm)]2 - 1.1 for f <= 200 MHz a (Hm) = 3.2*[log(11.75*Hm)]2 - 4.97for f >= 400 MHz B.1.2 Suburban Lsu (dB) = Lu - 2*[log(f/28)]2 - 5.4 B.1.3 Rural (Quasi-open) Lrqo (dB) = Lu - 4.78*[log(f)]2 + 18.33*log(f) - 35.94 B.1.4 Rural (Open Area) Lro (dB) = Lu - 4.78*[log(f)]2 + 18.33*log(f) - 40.94 B.2 COST 231-Hata Model [7] Frequency f: 1500 - 2000 MHz Base station height Hb: 30 - 200 m Mobile height Hm: 1 - 10 m Distance d: 1 - 20 km ETSI ETSI TR 101 362 V7.1.0 (2000-04) 21 (GSM 03.30 version 7.1.0 Release 1998) Large and small cells (i.e. base station antenna heights above roof-top levels of buildings adjacent to the base station). Urban areas (for rural areas the correction factors given in subparagraph 1.3 and 1.4 can be used up to 2000 MHz). Lu (dB) = 46.3 + 33.9*log(f) - 13.82*log(Hb) - a(Hm) + [44.9 - 6.55*log(Hb)]*log(d) + Cm with : a(Hm) = [1.1*log(f) - 0.7]*Hm - [1.56*log(f) - 0.8] Cm = 0 dB for medium sized city and suburban centres with moderate tree density Cm = 3 dB for metropolitan centres B.3 COST 231 Walfish-Ikegami Model [7] Frequency f: 800 - 2000 MHz Base station height Hb: 4 - 50 m Mobile height Hm: 1 - 3 m Distance d: 0.02 - 5 km Height of buildings Hroof (m) Width of road w (m) Building separation b (m) Road orientation with respect to the direct radio path Phi (°) Urban areas B.3.1 Without free line-of-sight between base and mobile (small cells) Lb = Lo + Lrts + Lmsd (or Lb = Lo for Lrts + Lmsd <= 0) with : B.3.1.1 Lo free-space loss Lo = 32.4 + 20*log(d) + 20*log(f) B.3.1.2 Lrts roof-top-to-street diffraction and scatter loss Lrts = -16.9 - 10*log(w) + 10 log(f) + 20*log(Hr - Hm) + Lcri with Lcri = -10 + 0.354*Phi for 0<= Phi < 35° Lcri = 2.5 + 0.075*(Phi-35) for 35<= Phi < 55° Lcri = 4.0 - 0.114*(Phi-55) for 55<= Phi <90° B.3.1.3 Lmsd multiscreen diffraction loss Lmsd = Lbsh + ka + kd*log(d) + kf*log(f) - 9*log(b) with Lbsh = -18*log(1 +Hb - Hroof) for Hb > Hroof = 0 for Hb <= Hroof ETSI ETSI TR 101 362 V7.1.0 (2000-04) 22 (GSM 03.30 version 7.1.0 Release 1998) ka = 54 for Hb > Hroof = 54 - 0.8*(Hb - Hroof) for d >= 0.5 and Hb <=Hroof = 54 - 0.8*(Hb - Hroof)*(d/0.5)for d<0.5 and Hb<=Hroof kd = 18 for Hb > Hroof = 18 - 15*(Hb - Hroof)/Hroof for Hb <= Hroof kf = -4 + 0.7*(f/925 - 1) for medium sized cities and suburban centres with moderate tree density = -4 + 1.5*(f/925 - 1) for metropolitan centres B.3.2 With a free line-of-sight between base and mobile (Street Canyon) Microcells (Base station antennas below roof top level) Lb = 42.6 + 26*log(d) + 20*log(f) for d >= 0.020 km ETSI ETSI TR 101 362 V7.1.0 (2000-04) 23 (GSM 03.30 version 7.1.0 Release 1998) Annex C: Path Loss vs Cell Radius 90 100 110 120 130 140 150 160 170 180 190 200 210 220 1 10 100 Cell radius (km) path loss (dB) Urban Urban Indoor Suburban Rural (quasi open) Rural (open) Figure 1: Path loss vs Cell Radius, BS height = 50 m, MS height = 1.5 m (GSM 900) ETSI ETSI TR 101 362 V7.1.0 (2000-04) 24 (GSM 03.30 version 7.1.0 Release 1998) 90 100 110 120 130 140 150 160 170 180 190 200 210 220 1 10 100 Cell radius (km) Path loss (dB) Urban Urban indoor Suburban Rural (quasi open) Rural (open) Figure 2: Path loss vs Cell Radius, BS height = 100 m, MS height = 1.5 m (GSM 900) ETSI ETSI TR 101 362 V7.1.0 (2000-04) 25 (GSM 03.30 version 7.1.0 Release 1998) 90 100 110 120 130 140 150 160 170 180 190 200 210 220 1 10 100 Cell Radius ( km) Path Loss (dB) Urban Urban indoor Rural indoor (quasi open) Rural (quasi open) Rural (open) Figure 3: Path loss vs Cell Radius, Urban BS height = 50 m, Rural BS height = 60 m, MS height = 1.5 m (DCS 1800) ETSI ETSI TR 101 362 V7.1.0 (2000-04) 26 (GSM 03.30 version 7.1.0 Release 1998) 0.1 0.5 1.0 3.0 100.0 110.0 120.0 130.0 140.0 150.0 160.0 170.0 P a t h l o s s d B GSM 900 DCS 1800 (medium sized cities and suburban centres) DCS 1800 (metropolitan centres) Cell Radius (km) Figure 4: Path loss vs Cell Radius for small cells (see section 3.4.2) ETSI ETSI TR 101 362 V7.1.0 (2000-04) 27 (GSM 03.30 version 7.1.0 Release 1998) Annex D: Planning Guidelines for Repeaters D.1 Introduction Repeaters can be used to enhance network coverage in certain locations. This annex provides guidelines for the design and installation of repeaters as network infrastructure elements. It covers both in building and outdoor applications. The principles within it may also form a basis for the design of repeaters for other applications within the system. D.2 Definition of Terms The situation where two BTSs and two MSs are in the vicinity of a repeater is shown in figure 5 below. BTSA and MSA belong to operator A and BTSB and MSB belong to a different operator, operator B. When planning repeaters, operators should consider the effects of the installation on both co-ordinated and uncoordinated operators. In the following sections, it is assumed that in the uncoordinated scenario, the repeater is planned and installed only for the benefit of operator A. Operator A is therefore, co-ordinated and operator B uncoordinated. In certain situations, operators may agree to share repeaters. Under these conditions, the repeater is planned and installed to provide benefit to all co-ordinated operators. If all operators within the GSM or DCS bands share a repeater, only the co-ordinated scenario exists. BTSA BTSB MAA MSB Repeater Figure 5: Repeater Scenario for two BTSs and two MSs The following abbreviations are used in this annex: G Repeater Gain PBTS BTS Output Power (in dBm) PMS MS Output Power (in dBm) PmaxDL Maximum Repeater Downlink Output Power (in dBm) PmaxUL Maximum Repeater Uplink Output Power (in dBm) NDL Repeater Downlink Noise Output in RX bandwidth (in dBm) NUL Repeater Uplink Noise Output in RX bandwidth (in dBm) SMS MS Reference Sensitivity (in dBm) SBTS BTS Reference Sensitivity (in dBm) C/Ic Carrier to Interference ratio for cochannel interference CL1 BTS to Repeater Coupling Loss (terminal to terminal) CL2 Repeater to MS Coupling Loss (terminal to terminal) CL3 The measured or estimated out of band coupling loss between a close coupled communication system and the repeater (terminal to terminal) M Number of carriers amplified by repeater ETSI ETSI TR 101 362 V7.1.0 (2000-04) 28 (GSM 03.30 version 7.1.0 Release 1998) Gsys The out of band repeater gain plus the gain of the external repeater antenna less the cable loss to that antenna. Gcom_3 The antenna gain of a close coupled communications system. Ms A safety margin for equipment used inside public buildings which should include the height gain of the external repeater antenna plus, if appropriate, the out of band building penetration loss. D.3 Gain Requirements The uplink and downlink gains should be such as to maintain a balanced link. The loss of diversity gain in the uplink direction may need to be considered. The gain of the repeater within its operating band should be as flat as possible to ensure that calls set up on a BCCH at one frequency can be maintained when the TCH is on a different frequency. The gain should be at least 15 dB smaller than the isolation between the antenna directed towards the BTS and the antenna directed towards the MSs, in order to prevent self oscillation. It is recommended to measure the isolation before installation of the repeater. Within the GSM/DCS1800 bands, but outside of the repeater operating range of frequencies, the installation of the repeater should not significantly alter the cellular design of uncoordinated operators. In the uncoordinated scenario, the repeater should not: i) amplify downlink signals from another operator such that MSs of that operator within a reasonable distance of the repeater select a remote cell amplified by the repeater as opposed to the local cell of that operator. ii) amplify uplink signals from other operators' MSs within a reasonable distance of that repeater and transmit them in such a direction as to cause more interference to other BTSs of that operator than other MSs in the area. For equipment used in public buildings where other communications systems could operate in very close vicinity (less than [5]m) of the repeater antennas, special care must be taken such that out of band signals are not re-radiated from within the building to the outside via the repeater system and vice versa. When using repeaters with an antenna mounted on the outside of the building, the effect of any additional height should be considered. If the close coupled communication system is usually constrained within the building, it may be necessary to consider the negation of building penetration loss when planning the installation. It is the operators responsibility to ensure that the out of band gain of the repeater does not cause disruption to other existing and future co-located radio communication equipment. This can be done by careful choice of the repeater antennas and siting or if necessary, the inclusion of in-line filters to attenuate the out of band signals from other systems operating in the close vicinity of the repeater. The following equation can be used to ensure an adequate safety margin in these cases: Gsys < Gcom_3 + CL3 -Ms (D.3.1) Where Gcom_3 is not known, a value of 2 dBi should be used. Where Ms is not known a value of 15 dB should be used. D.4 Spurious/Intermodulation Products When planning repeaters, operators should ensure that during operation, the spurious and intermodulation products generated by the repeater at uncoordinated frequencies are less than the limits specified in GSM 05.05. At co-ordinated frequencies, the intermodulation attenuation of the repeater in the GSM/DCS bands should be greater than the following limits: IM3 attenuationDL >= C/Ic + BTS power control range (D.4.1) IM3 attenuationUL >= PmaxUL - SBTS + C/Ic - CL1 (D.4.2) ETSI ETSI TR 101 362 V7.1.0 (2000-04) 29 (GSM 03.30 version 7.1.0 Release 1998) These limits apply in all cases except for initial random access bursts amplified by a repeater. D.5 Output Power/Automatic Level Control (ALC) The maximum repeater output power per carrier will be limited by the number of carriers to be enhanced and the third order intermodulation performance of the repeater. Operators should ensure that the requirements of section D.4 are met for the planned number of active carriers, the output power per carrier, and the repeater implementation. The number of simultaneously active carriers to be enhanced may be different in the uplink and downlink directions. When designing ALC systems, the following should be considered: i) When the ALC is active because of the close proximity of a particular MS, the gain is reduced for all MSs being served by the repeater, thereby leading to a possible loss of service for some of them. The operating region of the ALC needs to be minimized to reduce the probability of this occurrence. ii) The response of the ALC loop needs careful design. The ALC should not result in a significant distortion of the power/time profile of multiple bursts. iii) The ALC design should handle the TDMA nature of GSM signal so that it shall be effective for SDCCH and TCH transmissions with and without DTX. iv) The ALC may not operate quickly enough to cover the initial random access bursts sent by MSs. The intermodulation product requirement listed in section D.4 need not apply for these transient bursts. v) The ALC must have sufficient dynamic range to ensure that it maintains an undistorted output at the specified maximum power level when a fully powered-up MS is at the CL2min coupling loss. vi) In a non-channelized repeater the ALC will limit the total output power (i.e. peak of the sum of powers in each carrier). In most cases, the maximum ALC limit should be 3 dB above the power per carrier for two carriers whose third order intermodulation products just meet the requirements of section 4. When more than two carriers are simultaneously amplified, a higher limit may be employed provided the operator ensures that worst case intermodulation products meet the requirements of section D.4. D.6 Local oscillator sideband noise attenuation A local oscillator of a heterodyne type repeater with high sideband noise can cause a problem in uncoordinated scenarios. If the receive level from an uncoordinated MS is significantly higher than the receive level from the co-ordinated MS, both signals can be mixed with approximately the same level into the same IF, degrading the performance of the wanted signal. To avoid this, an IF type repeater equipped with a local oscillator should have a sideband noise attenuation at an offset of 600 kHz from the local oscillator frequency given by the equation: Sideband noise attenuation = CL2max - CL2min + C/Ic (D.6.1) D.7 Delay Requirements The ability of the MS to handle step changes in the time of arrival of the wanted signal is specified in GSM 05.05. When planning repeaters for contiguous coverage with other infrastructure elements, it is recommended that the additional delay through the repeater does not exceed the performance of the MS. The additional delay through the repeater should not cause a problem except in extreme multipath propagation conditions. The delay of the repeater will reduce the range of the cell in the area enhanced by the repeater. A delay of 8 microseconds is equivalent to a range reduction of 2.4 km. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 30 (GSM 03.30 version 7.1.0 Release 1998) D.8 Wideband Noise Wideband noise is a problem for uncoordinated scenarios. The noise level at the uncoordinated operators' frequencies needs to be such that an uncoordinated MS or BTS in the vicinity of the repeater is not desensitized as a result. The following equations provide the maximum noise output by the repeater in the receiver bandwidth for the downlink and uplink: NDL <= SMS - C/Ic + CL2Bmin (D.8.1) NUL <= SBTS - C/Ic + CL1Bmin (D.8.2) In co-ordinated scenarios, the maximum noise output by the repeater in the receiver bandwidth for the downlink direction is: NDL <= PmaxDL - BTS power control range - C/Ic (D.8.3) D.9 Outdoor Rural Repeater Example D.9.1 Rural repeater example for GSM 900 Rural repeaters are used to enhance areas of poor coverage due to terrain limitations. The repeater is located where a suitable signal strength can be received from the donor BTS. Typical signal levels received from the BTS at the input port to the repeater are in the range -50 to -70 dBm. This figure includes the height advantage and the gain of the antenna directed towards the BTS. The received signal is amplified and retransmitted towards the area of poor coverage. Figure 6 shows typical signal levels in the uplink and downlink directions. Two limiting cases for the MS to repeater coupling loss are shown. A diversity gain of 3 dB is assumed at the BTS making the effective reference sensitivity level -107 dBm. 100 dB BTS Repeater 70dB +43 dBm -57 dBm +13 dBm -57 dBm 70 dB 116 dB -103 dBm MS MS -76 dBm -107 dBm +24 dBm -7 dBm -31 dBm -77 dBm +39 dBm +39 dBm Figure 6: Uplink and downlink signal levels for a rural repeater The minimum coupling loss between the MS and the repeater is assumed to be 70 dB. D.9.1.1 Intermodulation products/ALC setting In this example an amplifier with a third order intercept (PTOI) of +50 dBm is assumed. The setting of the ALC for the two tone case is governed by the following equation (in dB): PALC = (2 PTOI + IM3)/3 + 3 (D.9.1.1) where IM3 is the limit specified in GSM 05.05. The inclusion of factor of 3 dB is described in section D.5. PALC = 24.3 dBm. Dependent on manufacturer guide-lines, the ALC setting may need to be reduced if many carriers are passing through the repeater. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 31 (GSM 03.30 version 7.1.0 Release 1998) In this example, the ALC is unlikely to be activated on the downlink. It could do so in applications with smaller BTS to repeater coupling loss. On the uplink, the ALC is activated when the MS is transmitting at full power, at the minimum coupling loss. The repeater gain is reduced so that the output power is limited to 24 dBm. This gain reduction may degrade the service given to other MSs served by the repeater until the BTS power control algorithm has reduced the MS output power. D.9.1.2 Wideband noise Wideband noise needs to be considered for both the uplink and the downlink for uncoordinated scenarios. A 70 dB coupling loss is assumed between the repeater and the uncoordinated MS and the repeater and the uncoordinated BTS. Then, using equations D.8.1 and D.8.2, the maximum noise power output is given by: NDL = NUL = -104 - 9 + 70 = -43 dBm The maximum noise figure required to achieve this noise level in both the uplink and down link directions is given by the following equation: F <= N - G - kT - B <= -43 - 70 - (-174) -53 <= 8 dB where F is the noise figure, N is the maximum noise level, G is the gain, kT is equal -174 dBm/Hz and B is the bandwidth conversion factor equal to 53 dB. D.10 Indoor Low Power Repeater Example D.10.1 Indoor repeater example for DCS 1800 Indoor repeaters are used to compensate for the losses associated with building attenuation. The signal level received from the BTS at the input port to the repeater is typically in the range -60 to -80 dBm. This figure includes the height advantage of placing an antenna on the roof of the building and the gain of the antenna directed towards the BTS. Figure 7 shows typical signal levels in the uplink and downlink directions. Two limiting cases for the MS to repeater coupling losses are shown. 110 dB BTS Repeater 45dB +39 dBm -71 dBm -26 dBm -56 dBm 40 dB 72 dB -98 dBm MS MS -91 dBm -107 dBm +19 dBm -3 dBm -10 dBm -42 dBm +30 dBm +30 dBm Figure 7: Uplink and downlink signal levels for indoor repeater The minimum coupling loss between the MS and the repeater is assumed to be 40 dB. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 32 (GSM 03.30 version 7.1.0 Release 1998) D.10.1.1 Intermodulation products/ALC setting Indoor repeaters are likely to be small low cost devices. Consequently, for indoor repeaters, the intermodulation performance is not as good as a rural repeater. In this example, an amplifier with a third order intercept (PTOI) of +40 dBm is assumed. For PTOI equal to 40 dBm and IM3 equal to -30 dBm, then using equation D.9.1.1: PALC = 19.7 dBm. On the uplink, the ALC is activated when the MS is transmitting at full power, at the minimum coupling loss. The repeater gain is reduced so that the output power is limited to 19 dBm. The received signal level at the BTS of -91 dBm is likely to be below the desired level which the MS power control algorithm seeks to maintain. Therefore, the MS is likely to remain powered up and the ALC will remain in operation continuously. Since, there is likely to be only one simultaneous user of this type of repeater, this is normally acceptable. D.10.1.2 Wideband noise Assuming a minimum coupling loss between the repeater and an unco-ordinated BTS of 65 dB, and between the repeater and an uncoordinated MS of 40 dBm, the following maximum noise levels are obtained using equations D.8.1 and D.8.2. NDL = -100 - 9 + 40 = -69 dBm NUL = -104 - 9 + 65 = -48 dBm The uplink noise level is easy to achieve in view of the low gain. The maximum noise figure required to achieve this noise level in down link directions is given by the following equation: F <= N - G - kT - B <= -69 - 40 - (-174) -53 <= 12 dB where F is the noise figure, N is the maximum noise level, G is the gain, kT is equal -174 dBm/Hz and B is the bandwidth conversion factor equal to 53 dB. D.11 Example for a Repeater System using Frequency Shift D.11.1 Example for GSM 900 Repeaters are used to enhance areas of poor coverage due to terrain limitations. The useable gain in an installation with a normal repeater is in generally limited in order to keep the repeater gain with a margin of 15 dB below the coupling of donor antenna and coverage antenna. Repeater systems using frequency shift relax the limitation in the usable gain of a normal repeater, due to different frequencies of the output signal and input signal. The repeater system consist of a master unit close to the BTS and at least one remote unit close to the area to be covered. The master unit amplifies the signals from the BTS and shifts them to other GSM channels called link channels in the allocated band of the operator. In the remote unit the link channels will be transferred to the original channels and amplified. A mobile station in the coverage area of the remote unit will detect the signals having passed the repeater system without any difference to a signal directly received from a BTS but the additional delay. The uplink channel settings of the repeater system follow exactly the settings of the downlink channels for the link path. Thus an uplink signal from a mobile in the coverage area of the repeater system will be received on its expected frequency by the BTS. Through application of sideband inversion technique on the downlink signals the BCCH cannot be decoded by a MS located between the master unit and the remote unit. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 33 (GSM 03.30 version 7.1.0 Release 1998) The master unit of the repeater system is located in the vicinity of a donor BTS with a relatively low coupling path loss of typically 30 dB to 60 dB. The downlink amplification is adjusted to the lowest necessary value in order to reduce the transmitted signal strength on the link channels of the master unit output. As a consequence of the high gain of the remote unit of the repeater sytem the distance to the master unit can be relatively high while the desired output power level is still maintained. The link path loss may vary up to 90 dB depending on the maximum gain of the remote unit. Oscillation of the repeater units is suppressed due to the shift between input and output frequencies and the decoupling betweeen coverage antenna and link antenna can be lower than the actual gain set in the remote unit. Therefore the effort for the installation at the remote unit location does not exceed the normal level. Figure 8 shows typical signal levels in the uplink and downlink directions.Two cases with maximum coupling loss of 135 dB and an assumed minimum coupling loss of 70 dB for the MS to repeater path are shown. BTS Repeater System Master Unit Repeater System Remote Unit MS DL 43 dBm -7 dBm -50 dB -90 dB -70 dB MS -135 dB 28 dBm G = 35 dB -62 dBm 33 dBm G = 95 dB -102 dBm -37 dBm UL -57 dBm -7 dBm -57 dBm G = 50 dB 33 dBm -37 dBm G = 88 dB 33 dBm 33 dBm -102 dBm -14 dBm -104 dBm -54 dBm -104 dBm Coupling Path Link Path Coverage Path Figure 8: Uplink and downlink signal levels for a repeater system using frequency shift D.11.1.1 Intermodulation products/ALC setting and levelling criteria In this example a repeater system with separate amplifier chain for each GSM channel is used. Thus a multiple carrier operation does not have an impact on the ALC settings in order to keep intermodulation products low as described in subchapter D.9.1.1. On the uplink, the ALC will be activated when the MS is transmitting at full power, at the minimum coupling loss of 70 dB. The repeater gain is reduced in this example by the ALC setting which is assumed to an output power of 33 dBm. This gain reduction may degrade the service given to other MSs served by the repeater until the BTS power control algorithm has reduced the MS output power. In addition to the definitions in subchapter D.2 the following term are used: GMU(DL,UL) Gain of master unit of repeater system in the downlink or uplink path GRU(DL,UL) Gain of remote unit of repeater system in the downlink or uplink path GTOT(DL,UL) Gain of the complete repeater system in one path calculated from BTS to remote unit repeater in the downlink or uplink path FTOT(UL) Noise figure of the complete repeater system including link path in the uplink path FMU(UL) Noise figure of the master unit of the repeater system in the uplink path FRU(UL) Noise figure of the remote unit of the repeater system in the uplink path CL2max Maximum Coupling loss between MS and repeater system CL(MU<->RU) Coupling loss between master unit and remote unit PRUmax(DL) Maximum output power of the remote unit in the downlink Mn Margin between repeater system output noise level at the BTS and equivalent input noise level of the BTS. This is a positive value if the repeater noise is lower. NTOT Noise level of repeater system at BTS input. As an example for the leveling of a repeater system using frequency shift see figure 8. Downlink levelling: In the downlink path it is intended to have a certain signal level retransmitted from the remote unit for coverage purposes. Thus the leveling of the repeater system is determined by the formula: ETSI ETSI TR 101 362 V7.1.0 (2000-04) 34 (GSM 03.30 version 7.1.0 Release 1998) GRU(DL) = PRUmax(DL) + CL(MU<->RU) + CL1 - PBTS - GMU(DL) In an installation the values for the coupling losses have to be measured. The remaining variable GMU(DL) has to be adjusted such, that the output power of the downlink signals of the master unit is as low as possible without danger of being interfered at the remote unit location. Uplink levelling: The adjustment of the uplink path gain is determined by the two demands: first the downlink and uplink path have to be balanced. Second, the receiver input shall not be desensitised by the repeater noise. The uplink gain between remote unit input and BTS input is GTOT(UL) = SBTS - PMS + CL2max = GRU(UL) + GMU(UL) - CL(MU<->RU) - CL1, which can be transformed to GRU(UL) = SBTS + CL1 + CL(MU<->RU) + CL2max - PMS - GMU(UL). This gives a relation for the gain setting of the remote unit with respect to the gain setting of the master unit when all coupling losses are determined. A further criteria for the leveling of the uplink is the total noise figure of the repeater system. In order to obtain a value close to the remote unit noise figure, the gain setting of the single repeater unit shall not be much lower than the path loss its output signal has to bridge. A desensitisation of the BTS will be prevented by keeping the uplink gain of the single repeater units close to the value of the path loss to be bridged. The noise at the BTS receiver input can be calculated from the total noise figure of the repeater system: FTOT(lin) = FRU(UL,lin) + ( FMU(UL,lin) - 1 ) / ( GRU(UL,lin) * CL(MU<->RU, lin) ). The variables marked by lin are linear and thus not logarithmic values. The noise at the BTS receiver input at room temperature for a given bandwidth of a GSM channel results in: NTOT = FTOT + GTOT(UL) + kT + B = FTOT + GTOT(UL) + (-174) + 53 This noise level has to be smaller than the equivalent noise at the receiver input: NTOT <= SBTS - C/Ic - Mn = SBTS - 9dB - 3dB A noise margin Mn equal to 3 dB is assumed. With a sensitivity of SBTS = -104 dBm the noise level of NTOT = - 116 dBm should not be exceeded. D.11.1.2 Wideband noise The repeater system using frequency shift is supposed to operate with dedicated channelised amplifiers. Therefore the uncoordinated scenario does not apply. D.11.1.3 Multipath environment Regions with strong multipath signals of direct signals from the BTS and delayed signals from the repeater system of nearly equal level should be avoided. One method to achieve this can be a coupling of the master unit of the repeater system to the BTS sector directed to the counterside of the area to be covered by the repeater system. Furthermore the geographic situation may prevent as well the occurrence of such strong multipath areas, so that as well onmidirectional cells as donor cells can be possible. D.12 Repeaters and Location Services (LCS) D.12.1 Uplink−TOA positioning method Figure 9 illustrates the potential problem which can occur when a MS near the service area of a wireless repeater should be located with the Uplink−TOA positioning method (see GSM 03.71 for details about the Uplink−TOA positioning ETSI ETSI TR 101 362 V7.1.0 (2000-04) 35 (GSM 03.30 version 7.1.0 Release 1998) method). It is assumed that a TOA Location Measurement Unit (LMU) is deployed at each BTS site. The LMUs colocated at BTS 1 and 2 will report TOA measurements τ1 and τ2 , which correspond to the propagation path length between the MS and BTS 1 and 2, respectively. An ambiguity will exist, when the RF path between the MS and BTS 3 can either be a direct path (τ3) or a path via the repeater (τR+τd+τRB), where τd is the delay of the repeater. BTS 3 BTS 1 BTS 2 LMU 1 LMU 3 LMU 2 MS τ1 τ2 τ3 Repeater for BTS 3 τR τd τRB LMU R Figure 9: Repeater Scenario for Uplink-TOA. An ambiguity free location solution can be obtained, if a TOA LMU is deployed at the repeater site. The LMUs which should participate in the position measurement procedure are selected by the Serving Mobile Location Centre (SMLC) (GSM 03.71). If a BTS has an associated repeater, then the SMLC should select the LMU colocated at the BTS site as well as the LMU colocated at its repeater site for TOA measurements. When a RF path exists between the MS and the repeater, the LMU R will report the TOA measurement τR, which corresponds to the propagation path length between the MS and the repeater. If LMU 3 and LMU R are reporting TOA measurements, then the SMLC should neglect the TOA measurement from LMU 3, since this TOA measurement can be based on (τR+τd+τRB) and will therefore result in a wrong location estimate. If the TOA LMU co-located at the repeater will not report a TOA measurement, it is obvious that no RF path between the MS and repeater exists. In that case, the TOA measurement from BTS 3 should be used. Other more intelligent processing can also be performed at the SMLC. To guarantee, that the Uplink−TOA positioning method works properly in radio environments with repeaters, a TOA LMU needs to be co located at the repeater site. If no LMU is co located at the repeater site, the SMLC should avoid selecting LMUs co located at a BTS which has an associated repeater. This requires that enough BTSs (LMUs) without repeaters are available in the vicinity of the MS and may therefore depend on the network. D.12.2 Enhanced Observed Time Difference positioning method Figure 10 illustrates the potential problem which can occur when a MS near the service area of a wireless repeater should be located with the Enhanced Observed Time Difference (E-OTD) positioning method (see GSM 03.71 for details about the E-OTD positioning method). Assuming for simplicity that BTSs transmit at the moment 0, the MS will receive signals from BTSs 1, 2 and 4 at moments τ1 , τ2 , and τ4, which correspond to the delays due to propagation paths between the MS and BTSs 1, 2 and 4, respectively. An ambiguity will exist, when the RF path between the BTS 3 and MS can either be a direct path (τ3) or a path via the repeater (τRB +τd+ τR), where τd is the delay of the repeater. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 36 (GSM 03.30 version 7.1.0 Release 1998) BTS 3 BTS 1 BTS 2 MS τ1 τ2 τ3 Repeater for BTS 3 τR τd τRB BTS 4 τ4 Figure 10: Repeater Scenario for E-OTD. An ambiguity free location solution can be obtained, if the MS measures sufficient number of BTSs so that the measurements concerning the BTS 3 (which can be direct measurements or via the repeater) can be dropped off. In the situation in Fig. 10, there are three other BTSs received by the MS, and the measurements from the BTS 3 can be omitted. Another possibility for ambiquity free location solution is to use other avilable information to judge whether the signal from the repeater or the direct signal from the BTS has been measured. For example the initial location estimate based on CI and TA information can be used to estimate whether the BTS or the repeater is more likely to be received by the MS. There can be also other implementation specific solutions in the SMLC. D.12.3 Radio Interface Timing measurements Figure 11 illustrates the potential problem which can occur when a LMU near the service area of a wireless repeater performs Radio Interface Timing (RIT) measurements (see GSM 03.71 for details about the RIT measurements). ETSI ETSI TR 101 362 V7.1.0 (2000-04) 37 (GSM 03.30 version 7.1.0 Release 1998) BTS 3 BTS 1 BTS 2 LMU τ1 τ2 τ3 Repeater for BTS 3 τR τd τRB Figure 11: Repeater Scenario for RIT measurements. The ambiguity problem applies also to LMUs that measure RIT information for E-OTD and Uplink-TOA methods, as well as for certain assisted GPS variants. In Figure 11 the LMU measures directly signals from BTSs 1 and 2 (BTS serving the LMU). However the RF path between the BTS 3 and LMU can either be a direct path (τ3) or a path via the repeater (τRB +τd+τR). The solution is that the operator selects such LMU sites that can only hear only the BTS or the repeater (e.g. based on network planning information). This can be enhanced by using directional antenna for the LMU, so that the antenna points towards e.g. the repeater, not the BTS, or vice versa. ETSI ETSI TR 101 362 V7.1.0 (2000-04) 38 (GSM 03.30 version 7.1.0 Release 1998) Annex E: Document change history SPEC SMG# CR PHASE VERS NEW_VERS SUBJECT 03.30 s25 A003 R97 5.0.0 Repeater Systems using Frequency Shift 03.30 s26 A003 R97 5.0.0 6.0.0 Repeater systems using Frequency Shift 03.30 s29 R98 6.0.1 7.0.0 Version 7.0.0 for Release '98 03.30 s31 A009 R98 7.0.0 7.1.0 LCS operation with repeaters ETSI ETSI TR 101 362 V7.1.0 (2000-04) 39 (GSM 03.30 version 7.1.0 Release 1998) History Document history V7.0.0 July 1999 Publication V7.1.0 April 2000 Publication
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1 Scope
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The present document specifies the RAN optimization and control related use cases that have been approved within O-RAN WG2. The purpose of the use cases is to help identify requirements for O-RAN defined interfaces and functions, specifically Non-RT RIC function and A1 and R1 interfaces, eventually leading to formal drafting of interface specifications. For each use case, the present document describes the motivation, resources, steps involved, and data requirements. Finally, the requirements clause details the functional and non-functional requirements derived from these use cases.
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2 References
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2.1 Normative references
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References are either specific (identified by date of publication and/or edition number or version number) or non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the referenced document (including any amendments) applies. Referenced documents which are not found to be publicly available in the expected location might be found in the ETSI docbox. NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee their long-term validity. The following referenced documents are necessary for the application of the present document. [1] 3GPP TS 22.261: "3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Service requirements for the 5G system; Stage 1", Release 16, October 2020. [2] 3GPP TS 23.501: "3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; System Architecture for the 5G System; Stage 2", Release 16, December 2020. [3] 3GPP TS 28.530: "3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Management and orchestration; Concepts, use cases and requirements", Release 16, December 2020. [4] 3GPP TS 28.541: "3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Management and orchestration; 5G Network Resource Model (NRM); Stage 2 and stage 3", Release 16, December 2020. [5] 3GPP TS 28.552: "3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Management and orchestration; 5G performance measurements" , Release 16, December 2020. [6] 3GPP TS 36.314: "3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); Layer 2 - Measurements", Release 16, July 2020. [7] 3GPP TS 38.314: "3rd Generation Partnership Project; Technical Specification Group Radio Access Network; NR; Layer 2 Measurements", Release 16, January 2021. [8] 3GPP TS 37.340: "E-UTRA and NR; Multi-connectivity", Release 16, October 2020. [9] GSMA: "Generic Network Slice Template Version 4.0", November 2020. [10] O-RAN.WG4.MP.0: "O-RAN Working Group 4 (Open Fronthaul Interfaces WG) Management Plane Specification". [11] 3GPP TS 32.423 "3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Telecommunication management; Subscriber and equipment trace; Trace data definition and management", Release 17, December 2022. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 8 [12] O-RAN. WG4.CUS.0: "O-RAN Working Group 4 (Open Fronthaul Interfaces WG) Control, User and Synchronization Plane Specification". [13] O-RAN.WG6.O2-GA&P: "O-RAN Working Group 6 O2 Interface General Aspects and Principles". [14] O-RAN.WG6.ORCH-USE-CASES: "O-RAN Working Group 6 Cloudification and Orchestration Use Cases and Requirements for O-RAN Virtualized RAN". [15] O-RAN.WG1.Slicing-Architecture: "O-RAN Work Group 1 (Use Cases and Overall Architecture) Slicing Architecture". [16] O-RAN.WG3.E2SM-KPM: "O-RAN Work Group 3 Near-Real-time RAN Intelligent Controller E2 Service Model (E2SM) KPM". [17] 3GPP TS 28.554: "3rd Generation Partnership Project; Technical Specification Group Radio Access Network; 5G; Management and orchestration; 5G end to end Key Performance Indicators (KPI)", Release 16, January 2021. [18] 3GPP TS 32.422: "3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Digital cellular telecommunications system (Phase 2+) (GSM); Universal Mobile Telecommunications System (UMTS); LTE; Telecommunication management; Subscriber and equipment trace; Trace control and configuration management", Release 16, January 2021. [19] 3GPP TS 37.320: "3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Universal Mobile Telecommunications System (UMTS); LTE; Universal Terrestrial Radio Access (UTRA) and Evolved Universal Terrestrial Radio Access (E-UTRA); Radio measurement collection for Minimization of Drive Tests (MDT); Overall description; Stage 2", Release 16, November 2020. [20] 3GPP TS 38.331: "3rd Generation Partnership Project; Technical Specification Group Radio Access Network; NR; Radio Resource Control (RRC); Protocol specification", Release 16, July 2020. [21] 3GPP TS 28.558: "3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Management and orchestration; UE level measurements for 5G system". [22] O-RAN TS: "A1 interface: Type Definitions" ("A1TD").
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2.2 Informative references
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References are either specific (identified by date of publication and/or edition number or version number) or non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the referenced document (including any amendments) applies. NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee their long-term validity. The following referenced documents may be useful in implementing an ETSI deliverable or add to the reader's understanding, but are not required for conformance to the present document. [i.1] 3GPP TR 21.905: "Vocabulary for 3GPP Specifications" [i.2] ETSI EN 302 637-2: "Intelligent Transport Systems (ITS); Vehicular Communications; Basic Set of Applications; Part 2: Specification of Cooperative Awareness Basic Service", Release 1, November 2010. [i.3] O-RAN.WG1.MMIMO-USE-CASES-TR-v00.13: "O-RAN Working Group 1, Massive MIMO Use Cases", Technical Report, March 2022. [i.4] ETSI ES 203 228: "Environmental Engineering (EE); Assessment of mobile network energy efficiency". ETSI ETSI TS 104 226 V10.1.0 (2025-08) 9 [i.5] ETSI ES 202 706-1: "Metrics and measurement method for energy efficiency of wireless access network equipment; Part 1: Power consumption - static measurement method". [i.6] 3GPP TR 38.913: "3rd Generation Partnership Project; Technical Specification Group Radio Access Network; 5G; Study on scenarios and requirements for next generation access technologies", Release 16, July 2020.
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3 Definition of terms, symbols and abbreviations
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3.1 Terms
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For the purposes of the present document, the terms given in 3GPP TR 21.905 [i.1] and the following apply. A term defined in the present document takes precedence over the definition of the same term, if any, in 3GPP TR 21.905 [i.1]. A1: interface between orchestration/NMS layer containing Non-RT RIC and eNB/gNB containing Near-RT RIC A1 policy: type of declarative policies expressed using formal statements that enable the Non-RT RIC function in the SMO to guide the Near-RT RIC function, and hence the RAN, towards better fulfilment of the RAN intent A1 enrichment information: information utilized by Near-RT RIC that is collected or derived at SMO/Non-RT RIC either from non-network data sources or from network functions themselves E2: interface between Near-RT RIC and the Multi-RAT CU protocol stack and the underlying RAN DU E2 node: O-CU-CP, O-CU-UP, O-DU, O-gNB, O-eNB energy consumption: integral of power consumption over time [i.5] energy efficiency: relation between the useful output and energy/power consumption [i.4] intents: declarative policy to steer or guide the behaviour of RAN functions, allowing the RAN function to calculate the optimal result to achieve stated objective Near-RT RIC: O-RAN Near-Real-Time RAN Intelligent Controller: A logical function that enables near-real-time control and optimization of RAN elements and resources via fine-grained data collection and actions over E2 interface Non-RT RIC: O-RAN Non-Real-Time RAN Intelligent Controller: A logical function in the SMO framework that enables non-real-time control and optimization of RAN elements and resources, AI/ML workflow including model training and updates, and policy-based guidance of applications/features in Near-RT RIC. The Non-RT RIC is comprised of the Non-RT RIC framework and Non-RT RIC applications (rApps) Non-RT RIC framework: functionality internal to the SMO framework that logically terminates the A1 interface and provides the R1services to rApps through the R1 interface O-CU: O-RAN Central Unit: A logical node hosting O-CU-CP and O-CU-UP O-CU-CP: O-RAN Central Unit - Control Plane: A logical node hosting the RRC and the control plane part of the PDCP protocol O-CU-UP: O-RAN Central Unit - User Plane: A logical node hosting the user plane part of the PDCP protocol and the SDAP protocol O-DU: O-RAN Distributed Unit: A logical node hosting RLC/MAC/High-PHY layers based on a lower layer functional split O-RU: O-RAN Radio Unit: A logical node hosting Low-PHY layer and RF processing based on a lower layer functional split. This is similar to 3GPP's "TRP" or "RRH" but more specific in including the Low-PHY layer (e.g. FFT/iFFT, PRACH extraction) O1: interface between management entities (NMS/EMS/MANO) and O-RAN managed elements, for operation and management, by which FCAPS management, software management, file management can be achieved ETSI ETSI TS 104 226 V10.1.0 (2025-08) 10 RAN: generally referred as Radio Access Network. In terms of the present document, any component below Near-RT RIC per O-RAN architecture, including O-CU/O-DU/O-RU rApp: Non-RT RIC application: An application designed to consume and /or produce R1 Services NOTE: rApps can leverage the functionality provided by the SMO and Non-RT RIC framework to deliver value added services related to intelligent RAN optimization and operation. R1 interface: interface between rApps and Non-RT RIC framework via which R1 Services can be produced and consumed R1 services: collection of services including, but not limited to, service registration and discovery services, authentication and authorization services, AI/ML workflow services, and A1, O1 and O2 interface related services
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3.2 Symbols
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Void.
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3.3 Abbreviations
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For the purposes of the present document, the abbreviations given in 3GPP TR 21.905 [i.1] and the following apply. An abbreviation defined in the present document takes precedence over the definition of the same abbreviation, if any, in 3GPP TR 21.905 [i.1]. 5QI 5G Quality of Service Identifier ASM Advanced Sleep Mode CAM Cooperative Awareness Message EC Energy Consumption EE Energy Efficiency eNB eNodeB (applies to LTE) ES Energy Saving FCAPS Fault, Configuration, Accounting, Performance, Security gNB gNodeB (applies to NR) KPI Key Performance Indicator m-MIMO Massive Multiple Input, Multiple Output MBB Mobile BroadBand NMS Network Management System QoE Quality of Experience RIC O-RAN RAN Intelligent Controller SINR Signal-to-Interference-plus-Noise Ratio SMO Service Management and Orchestration SSB Synchronization Signal Block
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4 Use cases
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4.1 Use case 1: Traffic steering use case
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4.1.0 Introduction
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This use case provides the motivation, description, and requirements for traffic steering use case, allowing operators to specify different objectives for traffic management such as optimizing the network/UE performance, or achieving balanced cell load. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 11
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4.1.1 Background and goal of the use case
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5G systems will support many different combinations of access technologies namely; LTE (licensed band), NR (licensed band), NR-U (unlicensed band), Wi-Fi® (unlicensed band). Several different multi-access deployment scenarios are possible with 5GC to support wide variety of applications and satisfy the spectrum requirements of different service providers: • Carrier aggregation between licensed band NR (primary cell) and NR-U (secondary cell) • Dual connectivity between licensed band NR (primary cell) and NR-U (secondary cell) • Dual connectivity between licensed band LTE (primary cell) and NR-U (secondary cell) The rapid traffic growth and multiple frequency bands utilized in a commercial network make it challenging to steer the traffic in a balanced distribution. Further in a multi-access system there is need to switch the traffic across access technologies based on changes in radio environment and application requirements and even split the traffic across multiple access technologies to satisfy performance requirements. The different types of traffic and frequency bands in a commercial network make it challenging to handle the complex QoS aspects, bearer selection Master Cell Group (MCG) bearer, Secondary Cell Group (SCG) bearer, split bearer), bearer type change for load balancing, achieving low latency and best in class throughput in a multi-access scenario with 5GC networks (as specified in 3GPP TS 37.340 [8]). Typical controls are limited to adjusting the cell reselection and handover parameters; modifying load calculations and cell priorities; and are largely static in nature when selecting the type of bearers and QoS attributes. Further, the Radio Resource Management (RRM) features in the existing cellular network are either cell-centric or UE-centric. Even in different areas within a cell, there are variations in radio environment, such as neighbouring cell coverage, signal strength, interference status, etc. However, base stations based on traditional control strategies treat all UEs in a similar way and both cell- and UE-centric algorithms do exist. Such current solutions suffer from following limitations: 1) It is hard to adapt the RRM control to diversified scenarios and optimization objectives. 2) The traffic management strategy is usually passive, rarely taking advantage of capabilities to predict network and UE performance. The strategy needs to consider aspects of steering, switching and splitting traffic across different access technologies in a multi-access scenario. 3) Non-optimal traffic management, with slow response time, due to various factors such as inability to select the right set of UEs for control action. This further results in non-optimal system and UE performance, such as suboptimal spectrum utilization, reduced throughput and increased handover failures. Based on the above reasons, the main objective of this use case is to allow operators to flexibly configure the desired optimization policies, utilize the right performance criteria, and leverage machine learning to enable intelligent and proactive traffic management.
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4.1.2 Entities/resources involved in the use case
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1) SMO (including Non-RT RIC): a) Retrieve necessary performance, configuration, and other data for defining and updating policies to guide the behaviour of traffic management function in Near-RT RIC. For example, the policy could relate to specifying different optimization objectives to guide the carrier/band preferences at per-UE or group of UE granularity. b) Retrieve necessary performance, configuration, and other data for performing data statistical analysis that will provide enrichment information for Near-RT RIC to assist in the traffic steering function. For example, this could be an analysis method to construct radio fingerprint based on UE measurement report with RSRP/RSRQ/CQI information for serving and neighbouring cells. c) Support communication of policies to Near-RT RIC. d) Support communication of measurement configuration parameters to RAN nodes. e) Support communication of enrichment information to Near-RT RIC, e.g. radio fingerprint information, etc. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 12 2) Near-RT RIC: a) Support interpretation and enforcement of policies from Non-RT RIC. b) Support using enrichment information to optimize control function, e.g. Near-RT RIC can use radio finger print to directly predict the inter-frequency cell measurement based on the intra-frequency cell measurement result to speed up the traffic steering with much reduced signalling overhead. 3) E2 nodes: a) Support data collection with required granularity to SMO over O1 interface.
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4.1.3 Solutions
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4.1.3.1 Traffic steering - policy part
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The context of traffic steering - policy part is captured in table 4.1.3.1-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 13 Table 4.1.3.1-1: Traffic steering - policy part Use Case Stage Evolution / Specification <<Uses>> Related use Goal Drive traffic management in RAN in accordance with defined intents, policies, and configuration. Actors and Roles Non-RT RIC: RAN policy control function. Near-RT RIC: RAN policy enforcement function. E2 nodes: Control plane and user plane functions. SMO/Collection & Control: Termination point for O1 interface. Assumptions • All relevant functions and components are instantiated. • A1 and interface connectivity is established with Non-RT RIC. • O1 interface connectivity is established with SMO/Collection & Control. Pre-conditions • Network is operational. • SMO/Collection & Control has established the data collection and sharing process, and Non-RT RIC has access to this data. • Non-RT RIC monitors the performance by collecting the relevant performance events and counters from E2 nodes via SMO/Collection & Control. Begins when Operator specified trigger condition or event is detected. Step 1 (O) If required, Non-RT RIC can request via SMO additional, more specific, performance measurement data to be collected from E2 nodes to assess the performance. Step 2 (M) Non-RT RIC decides an action and communicates relevant policies to Near-RT RIC over A1. The example policies can include: a) QoS targets b) Preferences on which cells to allocate control plane and user plane c) Preferences on user traffic distribution over primary cells and secondary cells d) Preferences on which carriers to be used for primary component carriers and secondary component carriers in multiple frequency coordination to optimize user traffic distribution Step 3 (M) The Near-RT RIC receives relevant information from Non-RT RIC over A1 interface, interprets the policies and enforces them. Step 4 (M) Non-RT RIC decides that conditions to continue the policy are no longer valid. Ends when Non-RT RIC deletes the policy. Exceptions None identified. Post Conditions Non-RT RIC monitors the performance by collecting the relevant performance events and counters from E2 nodes via SMO. Traceability • REQ-Non-RT-RIC-FUN1, REQ-Non-RT-RIC-FUN2, REQ-Non-RT- RIC-FUN3, REQ-Non-RT-RIC-FUN4, REQ-Non-RT-RIC-FUN5 • REQ-A1-FUN1 • REQ-Non-RT-RIC-NonFUN1, REQ-Non-RT-RIC-NonFUN2 Traffic steering use case flow diagram given in figure 4.1.3.1-1 illustrates the overall procedure for the traffic steering use case. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 14 Figure 4.1.3.1-1: Traffic steering use case flow diagram
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4.1.3.2 Traffic steering - EI part
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The context of traffic steering - EI part is captured in table 4.1.3.2-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 15 Table 4.1.3.2-1: Traffic steering - EI part Use Case Stage Evolution / Specification <<Uses>> Related use Goal Assist in traffic optimization in RAN in accordance with produced enrichment information. Actors and Roles Non-RT RIC: Enrichment information generation function. Near-RT RIC: Enrichment information consumption function. E2 nodes: Control plane and user plane functions. SMO/Collection & Control: Termination point for O1 interface. Assumptions • All relevant functions and components are instantiated. • A1 and interface connectivity is established with Non-RT RIC. • O1 interface connectivity is established with SMO/Collection & Control. Pre-conditions • Network is operational. • SMO/Collection & Control has established the data collection and sharing process, and Non-RT RIC has access to this data. • Non-RT RIC monitors the performance by collecting the relevant performance events and counters from E2 nodes via SMO/Collection & Control. • Non-RT RIC performs data analytics to generate/update the enrichment information. Begins when Operator specified trigger condition or event is detected. Step 1 (O) If required, Non-RT RIC can request via SMO additional, more specific, performance measurement data to be collected from E2 nodes to assess the performance. Step 2 (M) When receiving EI request/subscription message from Near-RT RIC, Non-RT RIC responds/notifies relevant enrichment information to Near-RT RIC over A1. The example enrichment information can include: a) Radio fingerprint Step 3 (M) The Near-RT RIC uses the enrichment information to optimize control function. Step 4 (M) In the EI subscription-notification mode, if there is an update on enrichment information. Non-RT RIC notifies the updated enrichment information to Near- RT RIC over A1 for optimizing control function. Stop When In the EI subscription-notification mode, EI notification continues until Non-RT RIC receives unsubscription message from Near-RT RIC. Exceptions None identified. Post Conditions Non-RT RIC monitors the performance by collecting the relevant performance events and counters from E2 nodes via SMO. Traceability • REQ-Non-RT-RIC-FUN1, REQ-Non-RT-RIC-FUN2, REQ-Non-RT- RIC-FUN3, REQ-Non-RT-RIC-FUN5, REQ-Non-RT-RIC-FUN7 • REQ-A1-FUN2 • REQ-Non-RT-RIC-NonFUN1, REQ-Non-RT-RIC-NonFUN2 Traffic steering use case flow diagram (with EI part) is given in figure 4.1.3.2-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 16 Figure 4.1.3.2-1: Traffic steering use case flow diagram (with EI part)
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4.1.4 Required data
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The measurement counters and KPIs (as defined by 3GPP and will be extended for O-RAN use cases) should be appropriately aggregated by cell, QoS type, slice, etc.: 1) Measurement reports with RSRP/RSRQ/CQI information for serving and neighbouring cells. In multi-access scenarios this will also include intra-RAT and inter-RAT measurement reports, cell quality thresholds, CGI reports and measurement gaps on per-UE or per-frequency. 2) UE connection and mobility/handover statistics with indication of successful and failed handovers, other metrics including threshold of number of UEs to trigger traffic management at O-DU, O-CU-CP, etc. 3) Cell load statistics such as information in the form of number of active users or connections, number of scheduled active users per TTI, PRB utilization, and CCE utilization, bearer metrics such as number of bearers to trigger traffic management at O-DU, O-CU-CP, etc. 4) Per user performance statistics such as PDCP throughput, RLC or MAC layer latency, DL throughput thresholds to trigger traffic management at O-DU, O-CU-CP, etc.
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4.1.5 A1 usage example
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An example scenario is here used to describe the use of A1 for traffic management, implying the Non-RT RIC sending policies for allocation of the control plane (RRC) and the user plane for different services, identified by their 5QI. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 17 In the scenario a UE with UEid=1, belonging to a subnet slice identified by S-NSSAI=1, having a voice (5QI=1) and an MBB (5QI=9) connection established, enters an area covered by four frequency bands. The Non-RT RIC understands the requirements and characteristics of the services and decides to let the voice and RRC connection reside on the low band (here covered by a macro cell B becoming the PCell), while the MBB connection should preferably use the higher band (here provided by a smaller cell C and D becoming the SCells) and avoid the low band if possible. Cell A is used for MBB if required for coverage reasons. Policies are sent to any cell of concern, e.g. where the UE resides and can move. The desired use of the cells is shown in figure 4.1.5-1. Figure 4.1.5-1: Desired use of the cells Two policies over A1 are needed to accomplish the desired behaviour, described in JSON format below. Note that as part of the scope, the cell_id is optional, and if omitted it is up to the Near-RT RIC to locate the UE and there enforce the policy. { "policy_id": "1", "scope": { "ue_id": "1", "slice_id": "1", "qos_id": "1", "cell_id": "X" // Policy for Cell X, where X is one of A, B, C or D }, "statement": { "cell_id_list": "B", "preference": "Shall", "primary": true // Control plane on Cell B (becoming PCell) }, "statement": { "cell_id_list ": "B", "preference": "Shall", "primary": true // Voice on Cell B ETSI ETSI TS 104 226 V10.1.0 (2025-08) 18 } } { "policy_id": "2", "scope": { "ue_id": "1", "slice_id": "1", "qos_id": "9", "cell_id": "X" // Policy for Cell X, where X is one of A, B, C or D }, "statement": { "cell_id_list ": {"B", "A"}, "preference": "Avoid", "primary": false // Avoid MBB on Cell A and Cell B }, "statement": { "cell_id_list": {"C", "D"}, "preference": "Prefer", "primary": false // Prefer MBB on Cell C and Cell D } } Besides the cell level preference policy, there are also carrier level preference policy for the traffic steering use case. Taking the above scenario as an example, the UE with UEid=1, belonging to a subnet slice identified by S-NSSAI=1, having a voice (5QI=1) and an MBB (5QI=9) connection established, enters the area covered by four cells identified by cell A, cell B, cell C and cell D, respectively. Assuming that cell A and cell B work on the same frequency carrier which can be identified by Arfcn_1, cell C and cell D work on the same frequency carrier which can be identified by Arfcn_2. Carrier Arfcn_1 is in low frequency and have narrow bandwidth and adapt to voice (5QI=1) connection. Carrier Arfcn_2 is in high frequency and have wide bandwidth and adapt to MBB (5QI=9) connection, meanwhile, avoid connection to the low frequency bands. The following policies are needed to accomplish this as described in JSON format below. { "policy_id": "1", "scope": { "ue_id": "1", "slice_id": "1", "qos_id": "1", "cell_id": "X" // Policy for Cell X, where X is one of A, B, C or D }, "statement": { "carrier_id_list": "Arfcn_1", ETSI ETSI TS 104 226 V10.1.0 (2025-08) 19 "preference": "Prefer", "primary": true // Control plane on Carrier Arfcn_1 (becoming Primary Component Carrier) }, } { "policy_id": "2", "scope": { "ue_id": "1", "slice_id": "1", "qos_id": "9", "cell_id": "X" // Policy for Cell X, where X is one of A, B, C or D }, "statement": { "carrier_id_list ": "Arfcn_1", "preference": "Avoid", "primary": false // Avoid MBB on Carrier Arfcn_1, and no carrier in the carrier_id_list is to be used as secondary component carrier. That is said, Arfcn_1 is not used as secondary component carrier, because it is already used for primary component carrier as the policy 1 stated. }, "statement": { "carrier_id_list": "Arfcn_2", "preference": "Prefer", "primary": false // Prefer MBB on Carrier Arfcn_2, and Arfcn_2 is used as secondary component carrier } }
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4.1.6 Enrichment information example
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Radio fingerprint is composed of multiple virtual grids. The virtual grids are constructed based on the historical report of intra-frequency and inter-frequency measurement results of UEs from both the serving cell and the neighbour cell. The serving cell is divided into multiple grids according to the signalling measurement difference. It can be seen as a kind of different space partition method which is different with the traditional space partition method based on geographical location. To construct the radio fingerprint, the grid index and the grid attributes need to be defined. The grid index is to identify a specific virtual grid and this index consists of cell ID and corresponding coverage quality, e.g. RSRP segment ID, of at least three intra-frequency cells. The grid attributes are used to describe the wireless characteristics of the grid, such as coverage of inter-frequency neighbour cells, including RSRP, Reference Signal Receiving Quality (RSRQ), Received Signal Strength Indication (RSSI), Channel Quality Indicator (CQI), Modulation and Coding Scheme (MCS), beam ID, etc., handover performance indicators, and so on. The virtual grids of the radio fingerprint are shown in figure 4.1.6-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 20 Figure 4.1.6-1: Illustration of the virtual grid of radio fingerprint
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4.1.7 A1 usage example in multi-access environment
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The Non-RT RIC can send policies for traffic distribution in a multi-access environment based on UE characteristics and traffic patterns for different services that can be identified by their 5QI. The following example scenario illustrates this, in which there are three UEs with the following characteristics. UE Identifier UE Id=1, S-NSSAI =1 UE Id=2, S-NSSAI =2 UE Id=3, S-NSSAI =3 User Traffic 5QI=1: Voice 5QI=8: FTP, Email 5QI=1: Voice 5QI=8: Email 5QI=83: Advanced driving 5QI=1: Voice 5QI=8: Progressive video 5QI=8: File sharing Mobility Pattern Stationary High mobility Low mobility The UEs are in an area covered by three frequency bands identified by cell A, cell B and cell C respectively. Cell A is the macro licensed cell with the best coverage. Cell B is the unlicensed cell with limited coverage and cell C is a licensed cell with narrow bandwidth but provides greater coverage area than cell B. The cell layout for multi-access use case is shown in figure 4.1.7-1. Cell B Unlicensed band Cell A Licensed band Cell C Narrow bandwidth licensed band UE Id=1 UE Id=3 UE Id=2 High Mobility UE Figure 4.1.7-1: Cell layout for multi-access use case From a traffic distribution perspective, since UE with UE Id=1 is a stationary UE the FTP and email traffic with (5QI=8) should preferably be routed over secondary unlicensed cell B and should avoid licensed cells, cell A and cell C. The voice traffic should be routed over cell A. For UE with UE Id=2, since it is a highly mobile UE, all the traffic should be routed over licensed cells, preferably cell A to avoid disruption in connections. However, if there is a shortage of bandwidth in cell A, the email traffic (5QI=8) can be routed over unlicensed band (cell B). Given that this is a high mobility UE, there can be a policy that a minimum of 50 % and maximum of 70 % of all traffic from this UE should be routed over cell A which should be the primary cell and remaining can be routed over secondary cell. For UE with UE Id=3, since it is a low mobility UE both the progressive video (5QI=8) and file sharing (5QI=8) should be routed over unlicensed band (cell B). The voice traffic should be routed over cell A. The following policies are needed to accomplish this as described in JSON format below: • Policy Id 1: For group of UEs with UE Id, 1, 2 and 3. It sets the preference for voice traffic (5QI=1) on cell A for all the UEs. Further, dual connectivity should be enabled for all these UEs whenever possible. • Policy Id 2: For group of UEs with UE Id, 1 and 3. It sets the preference for all traffic with (5QI=8) on cell B for both the UEs and also avoids cell A and cell C for routing this traffic. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 21 • Policy Id 3: For UE with UE Id=2. It sets the preference for advanced driving traffic with (5QI=83) on cell A and C and also avoids cell B for routing this traffic. • Policy Id 4: For UE with UE Id=2. It sets the preference for email traffic with (5QI=8) on cell A and C for the high mobility UE. However, it does not avoid use of cell B for routing this traffic in case of bandwidth limitation. • Policy Id 5: For UE with UE Id=2. It sets the preference that minimum of 50 % and a maximum of 70 % of all traffic from this UE should be routed through cell A for this UE. { "group_id": "1", "ue_id_list": {"1","2","3"} // Define group_1 list of UEs, 1, 2 and 3 "policy_id": "1", "scope": { "group_id": "1", "qos_id": "1", "cell_id": "X" // Policy for Cell X, where X is one of A, B, or C for this group of UEs }, "statement": { "cell_id_list": "A", "preference": "Prefer", "dual connectivity": true, // dual connectivity is preferred for UEs in group 1 "primary": true // Cell A is preferred primary cell for 5QI=1 (Voice), for UEs in group 1 } } { "group_id": "2", "ue_id_list": {"1","3"} // Define group_1 list of UEs, 1 and 3 "policy_id": "2", "scope": { "group_id": "2", "qos_id": "8", "cell_id": "X" // Policy for Cell X, where X is one of A, B, or C }, "statement": { "cell_id_list": {"A", "C"}, "preference": "Avoid", "primary": false // Avoid 5QI=8 traffic on Cell A and C }, ETSI ETSI TS 104 226 V10.1.0 (2025-08) 22 "statement": { "cell_id_list": {"B"}, "preference": "Prefer", "primary": false // Prefer 5QI=8 traffic on Cell B for stationary and low mobility UEs } } { "policy_id": "3", "scope": { "ue_id": "2", "slice_id": "2", "qos_id": "83", "cell_id": "X" // Policy for Cell X, where X is one of A, B, or C }, "statement": { "cell_id_list ": {"B"}, "preference": "Avoid", "primary": false // Avoid 5QI=83 traffic on Cell B }, "statement": { "cell_id_list": {"A", "C"}, "preference": "Prefer", "primary": true // Prefer 5QI=83 traffic on Cell A or C for high mobility UE } } { "policy_id": "4", "scope": { "ue_id": "2", "slice_id": "2", "qos_id": "8", "cell_id": "X" // Policy for Cell X, where X is one of A, B, or C }, "statement": { "cell_id_list": {"A", "C"}, "preference": "Prefer", "primary": true // Prefer 5QI=8 traffic on Cell A or C and don't avoid cell B } ETSI ETSI TS 104 226 V10.1.0 (2025-08) 23 } { "policy_id": "5", "scope": { "ue_id": "2", "slice_id": "2", "traffic distribution": "X" // Policy for traffic distribution }, "statement": { "cell_id_list": {"A"}, "preference": "Prefer", "minimum": "50%", "maximum": "70%", // Prefer 50-70% of traffic distribution on cell A for this UE } }
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4.2 Use case 2: QoE use case
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4.2.0 Introduction
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This use case provides the background and motivation for the O-RAN architecture to support real-time QoE optimization. Moreover, some high-level description and requirements over Non-RT RIC, A1 and E2 interfaces are introduced.
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4.2.1 Background and goal of the use case
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The highly demanding 5G native applications such as cloud VR are both bandwidth consuming and latency sensitive. However, for such traffic-intensive and highly interactive applications, current semi-static QoS framework cannot efficiently satisfy diversified QoE requirements especially taking into account potentially significant fluctuation of radio transmission capability. It is expected that QoE estimation/prediction from application level can help deal with such uncertainty and improve the efficiency of radio resources, and eventually improve user experience. The main objective is to ensure QoE optimization be supported within the O-RAN architecture and its open interfaces. Multi-dimensional data, e.g. user traffic data, QoE measurements, network measurement report, can be acquired and processed via ML algorithms to support traffic recognition, QoE prediction, and QoS enforcement decisions. ML models can be trained offline and model inference will be executed in a real-time manner. Focus should be on a general solution that would support any specific QoE use case (e.g. cloud VR, video, etc.).
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4.2.2 Entities/resources involved in the use case
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1) Non-RT RIC: a) Retrieve necessary QoE related measurement metrics from network level measurement report and SMO (can acquire data from application) for constructing/training relevant AI/ML model that will be deployed in Near-RT RIC to assist in the QoE optimization function. For example, this could be application classification, QoE prediction, and available bandwidth prediction. b) Training of potential ML models for predictive QoE optimization, which can respectively autonomously recognize traffic types, predict quality of experience, or predict available radio bandwidth. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 24 c) Send policies/intents to Near-RT RIC to drive the QoE optimization at RAN level in terms of expected behaviour. 2) Near-RT RIC: a) Support update of AI/ML models from Non-RT RIC. b) Support execution of the AI/ML models from Non-RT RIC, e.g. application classification, QoE prediction, and available bandwidth prediction. c) Support interpretation and execution of intents and policies from Non-RT RIC to derive the QoE optimization at RAN level in terms of expected behaviour. d) Sending QoE performance report to Non-RT RIC for evaluation and optimization. 3) E2 nodes: a) Support network state and UE performance report with required granularity to SMO over O1 interface. b) Support QoS enforcement based on messages from A1/E2, which are expected to influence RRM behaviour.
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4.2.3 Solutions
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4.2.3.1 Model training and distribution
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The context of model training and distribution is captured in table 4.2.3.1-1. Table 4.2.3.1-1: Model training and distribution Use Case Stage Evolution / Specification <<Uses>> Related use Goal Model training and distribution. Actors and Roles Non-RT RIC, Near-RT RIC, SMO, application server Assumptions • All relevant functions and components are instantiated. • A1/O1 interface connectivity is established with Non-RT RIC. Pre-conditions Near-RT RIC and Non-RT RIC are instantiated with A1 interface connectivity being established between them. Begins when Operator specified trigger condition or event is detected. Step 1 (M) QoE related measurement metrics from SMO (can acquire data from application) and network level measurement report either for instantiating training of a new ML model or modifying existing ML model. Step 2 (M) Non-RT RIC does the model training, obtains QoE related models, and can deploy QoE policy model internally. An example of QoE-related models that can be used at the Near-RT RIC is provided as follows: a) Application classification model (optional and can refer to 3rd party's existing functionality) b) QoE prediction model c) QoE policy model d) Available BW prediction model Step 3 (M) Non-RT RIC deploys/updates the AI/ML model in the Near-RT RIC via O1. Step 4 (M) Near-RT RIC stores the received QoE related ML models in the ML model inference platform and based on requirements of ML models. Step 5(O) If required, Non-RT RIC can configure specific performance measurement data to be collected from RAN to assess the performance of AI/ML models and update the AI/ML model in Near-RT RIC based on the performance evaluation and model retraining. Ends when Operator specified trigger condition or event is satisfied. Exceptions None. Post Conditions Near-RT RIC stores the received QoE related ML models in the ML Model inference platform and execute the model for QoE optimization function in Near-RT RIC. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 25 Use Case Stage Evolution / Specification <<Uses>> Related use Traceability • REQ-Non-RT-RIC-FUN1, REQ-Non-RT-RIC-FUN3, REQ-Non- RT-RIC-FUN4, REQ-Non-RT-RIC-FUN5 • REQ-A1-FUN1, REQ-A1-FUN2, REQ-A1-FUN4 The QoE use case flow diagram - model training and distribution/update is given in figure 4.2.3.1-1. Figure 4.2.3.1-1: QoE use case flow diagram - model training and distribution/update
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4.2.3.2 Policy generation and performance evaluation
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The context of policy generation and performance evaluation is captured in table 4.2.3.2-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 26 Table 4.2.3.2-1: Policy generation and performance evaluation Use Case Stage Evolution / Specification <<Uses>> Related use Goal Policy generation and performance evaluation. Actors and Roles Non-RT RIC, Near-RT RIC, SMO. Assumptions • All relevant functions and components are instantiated. • A1/O1 interface connectivity is established with Non-RT RIC. Pre-conditions QoE related models have been deployed in Non-RT RIC and Near-RT RIC respectively. Begins when The network operator/manager want to generate QoE policy or optimize QoE related AI/ML models. Step 1 (M) Non-RT RIC evaluates the collected data and generates the appropriate QoE optimization policy. Step 2 (M) Non-RT RIC sends the QoE optimization policy to Near-RT RIC via A1 interface. Step 3 (M) Near-RT RIC receives the policy from the Non-RT RIC over the A1 interface. And the Near-RT RIC inferences the QoE related AI/ML models and converts policy to specific E2 control or policy commands. Step 4 (M) Near-RT RIC sends the E2 control or policy commands towards RAN for QoE optimization. Step 5 (M) RAN enforces the received control or policy from the Near-RT RIC over the E2 interface. Step 6 (O) If required, Non-RT RIC can receive policy feedback from Near-RT RIC and performance measurement data collected from SMO to assess the performance of the QoE optimization function in Near-RT RIC, or to assess the outcome of the applied A1 policies. And then update A1 policy and E2 control or policy. Ends when Operator specified trigger condition or event is satisfied. Exceptions None. Post Conditions Non-RT RIC monitors the performance of the QoE optimization related function in Near-RT RIC by collecting and monitoring the relevant performance KPIs and counters from RAN. Traceability • REQ-Non-RT-RIC-FUN1, REQ-Non-RT-RIC-FUN3, REQ-Non- RT-RIC-FUN4, REQ-Non-RT-RIC-FUN5. • REQ-A1-FUN1, REQ-A1-FUN2, REQ-A1-FUN4. The QoE use case flow diagram - policy generation and performance evaluation is given in figure 4.2.3.2-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 27 Figure 4.2.3.2-1: QoE use case flow diagram - policy generation and performance evaluation
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4.2.4 Required data
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Multi-dimensional data are expected to be retrieved by Non-RT RIC for AI/ML model training and policies/intents generation: 1) Network level measurement report, including: - UE level radio channel information, mobility related metrics - L2 measurement report related to traffic pattern, e.g. throughput, latency, packets per-second, inter frame arrival time - RAN protocol stack status: e.g. PDCP buffer status - Cell level information: e.g. DL/UL PRB occupation rate 2) QoE related measurement metrics collected from SMO (can acquire data from application or network). 3) User traffic data, which can be obtained via a proprietary interface from existing data collection equipment and is currently out of the scope of A1 or E2.
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4.2.5 A1 usage example
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There are 3 examples to explain how A1 policy woks for QoE optimization. One is for ue_id (100), slice_id (1) and qos_id (5QI =50), the target QoE score (for example video MOS 80) should be satisfied. { ETSI ETSI TS 104 226 V10.1.0 (2025-08) 28 "policy_id": "1", "scope": { "ue_id": "100", "slice_id": "1", "qos_id": "50" }, "statement": { "qoe_score": "80" } } The second example is to regulate specific QoE targets, for example, initial buffering time for video streaming is required within 2 seconds, rebuffering frequency is 2 times and stalling ratio is 5 % for a customized time window (e.g. 30 seconds). { "policy_id": "2", "scope": { "ue_id": "101", "slice_id": "1", "qos_id ": "51" }, "statement": { "initial_buffering": "2", "reBuffFreq":"2", "stallRatio": "5" } } The specific user id need not be required, and only slice_id and flow_id are required for specific QoE targets. { "policy_id": "3", "scope": { "slice_id": "1", "flow_id": "51" }, "statement": { "initial_buffering":"2", "reBuffFreq":"2", "stallRatio": "5" } } ETSI ETSI TS 104 226 V10.1.0 (2025-08) 29
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4.3 Use case 3: QoS based resource optimization
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4.3.0 Introduction
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This use case provides the background and motivation for the O-RAN architecture to support RAN QoS based resource optimization. Moreover, some high-level description and requirements over Non-RT RIC and A1 interfaces are introduced.
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4.3.1 Background and goal of the use case
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QoS based resource optimization can be used when the network has been configured to provide some kind of preferential QoS for certain users. One such scenario can be related to when the network has been configured to support e2e slices. In this case, the network has functionality that ensures resource isolation between slices as well as functionality to monitor that slice Service Level Specifications (SLS) are fulfilled. In RAN, it is the scheduler that ensures that Physical Resource Block (PRB) resources are isolated between slices in the best possible way and also that the PRB resources are used in an optimal way to best fulfil the SLS for different slices. The desired default RAN behaviour for slices is configured over O1. For example, the ratio of physical resources (PRBs) reserved for a slice is configured at slice creation (instantiation) over O1. Also, QoS can be configured to guide the RAN scheduler how to (in real-time) allocate PRB resources to different users to best fulfil the SLS of a specific slice. In the NR NRM this is described by the resource partition attribute. Instantiation of a RAN sub-slice will be prepared by rigorous planning to understand to what extent deployed RAN resources will be able to support RAN sub-slice SLS. Part of this procedure is to configure RAN functionality according to above. With this, a default behaviour of RAN is obtained that will be able to fulfil slice SLSs for most situations. However, even through rigorous planning, there will be times and places where the RAN resources are not enough to fulfil SLS given the default configuration. To understand how often (and where) this happens, the performance of a RAN slice will continuously be monitored by SMO. When SMO detects a situation when RAN SLS cannot be fulfilled, Non-RT RIC can use A1 policies to improve the situation. To understand how to utilize A1 policies and how to resolve the situation, the Non RT-RIC will use additional information available in SMO. Take an emergency service as an example of a slice tenant. For this example, it is understood (at slice instantiation) that 50 % of the PRBs in an area can be enough to support the emergency traffic under normal circumstances. Therefore, the ratio of PRBs for the emergency users is configured to 50 % as default behaviour for the pre-defined group of users belonging to the emergency slice. Also, QoS is also configured in core network and RAN so that video cameras of emergency users get a minimum bitrate of 500 kbps. Now, suppose a large fire is ongoing and emergency users are on duty. Some of the personnel capture the fire on video on site. The video streams are available to the emergency control command. Because of the high traffic demand in the area from several emergency users (belonging to the same slice), the resources available for the emergency slice is not enough to support all the traffic. In this situation, the operator has several possibilities to mitigate the situation. Depending on SLAs towards the emergency slice compared to SLAs for other slices, the operator could reconfigure the amount of PRB reserved to emergency slice at the expense of other slices. However, there is always a risk that emergency video quality is not good enough irrespective if all resources are used for emergency users. It might be that no video shows sufficient resolution due to resource limitations around the emergency site. In this situation, the emergency control command decides, based on the video content, to focus on a selected video stream to improve the resolution. The emergency control system gives the information about which users to up- and down-prioritize to the E2E slice assurance function (through e.g. an edge API) of the mobile network to increase bandwidth for selected video stream(s). Given this additional information, the Non-RT RIC can influence how RAN resources are allocated to different users through a QoS target statement in an A1 policy. By good usage of the A1 policy, the emergency control command can ensure that dynamically defined group of UEs provides the video resolution that is needed. The use case can be summarized as per below: 1) A fire draws a lot of emergency personnel to an area. 2) Because of this, RAN resources becomes congested which affects the video quality for all video feeds in the area. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 30 3) The emergency control command have 5 active video feeds and selects one video feed which is of specific interest. 4) The emergency control command requests higher resolution of a selected feed, while demoting the other. 5) With this information, the Non-RT RIC will evaluate how to ensure higher bandwidth for the feed selected by emergency control command (and lower for other feeds). 6) The Non-RT RIC updates the policy for the associated UEs in the associated Near-RT RIC over the A1 interface. 7) Near-RT RIC enforce the modified QoS target for the associated UEs over the E2 interface to fulfil the request. 8) The emergency control command experiences a higher resolution of the selected video feed.
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4.3.2 Entities/resources involved in the use case
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1) Non-RT RIC: a) Monitor necessary QoS related metrics from network function and other SMO functions. b) Send policies to Near-RT RIC to drive QoS based resource optimization at RAN level in terms of expected behaviour. 2) Near-RT RIC: a) Support interpretation and execution of A1 policies for QoS based resource optimization. 3) E2 nodes: a) Support network state and UE performance report with required granularity to SMO over O1 interface. b) Support QoS enforcement based on messages from E2, which are expected to influence RRM behaviour.
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4.3.3 Solutions
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4.3.3.1 QoS based resource optimization
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The context of QoS based resource optimization is captured in table 4.3.3.1-1. Table 4.3.3.1-1: QoS based resource optimization Use Case Stage Evolution / Specification <<Uses>> Related use Goal Drive QoS based resource optimization in RAN in accordance with defined policies and configuration. Actors and Roles Non-RT RIC: Creates A1 policies. Near-RT RIC: Enforces A1 policies. RAN: Policy enforcement. SMO: Termination point for O1 interface. Assumptions All relevant functions and components are instantiated and configured according wanted default behaviour. A1 interface connectivity is established with Non-RT RIC. O1 interface connectivity is established with SMO. The default configuration will handle most situations. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 31 Use Case Stage Evolution / Specification <<Uses>> Related use Pre-conditions Network is operational with default configuration. SMO has established the data collection and sharing process, and Non-RT RIC has access to this data. Non-RT RIC analyses the data from RAN to understand the current resource consumption. Begins when Non-RT RIC observes that resources are close to congestion in a certain area. Step 1 (O) If needed, Non-RT RIC orders additional RAN observability, SMO configures additional observability over O1. Step 2 Non-RT RIC evaluates RAN resource utilization for all users in a slice in specific area. Step 3 Non-RT RIC asks for additional information from additional SMO functionality, e.g. E2E slice assurance function. Step 4 Non-RT RIC determines dynamic group of users for which QoS target shall be changed. Step 5 Non-RT issues A1 policy/policies with QoS target based on information from other SMO functionality. Ends when Non-RT RIC (through O1 observability) understands that situation of resource constraints within the slice is resolved, and the deployed policies are deleted over A1. Exceptions None identified. Post Conditions Non-RT RIC monitors the performance by collecting the relevant performance events and counters from E2 nodes via SMO. Traceability • REQ-Non-RT-RIC-FUN1, REQ-Non-RT-RIC-FUN2, REQ-Non-RT- RIC-FUN3, REQ-Non-RT-RIC-FUN4, REQ-Non-RT-RIC-FUN5. • REQ-A1-FUN1. The flow diagram of the QoS based resource optimization use case is given in figure 4.3.3.1-1. Figure 4.3.3.1-1: Flow diagram of QoS based resource optimization use case ETSI ETSI TS 104 226 V10.1.0 (2025-08) 32
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4.3.4 Required data
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For this use case, different kind of observability need to be reported to Non-RT RIC. First Non-RT RIC shall monitor resource consumption in the area. As long as resource consumption is low, the RAN scheduler will be able to give all users in an area the needed resources. When resource consumption in an area increases above a threshold, there is risk of that the default configuration of RAN will not be enough to fulfil the requirements. At this point, the Non-RT RIC need to be able to configure more detailed reporting for individual UEs that the Non-RT RIC is interested in. This detailed observability should provide the Non RT RIC better insight in performance for specific users and therefore includes observability of e.g. user throughput and delay. With this more detailed observability, the Non-RT RIC can understand when pre-configured priorities are not enough for the scheduler to solve the problem and when additional (non-RAN) information to solve the prioritization is needed.
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4.3.5 A1 usage example
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Example scenario • One emergency RAN sub-slice defined (S-NSSAI=1) with a ratio of 50 % configured. 5QI=74 configured for a minimum bitrate of 500 kbps. • 4 UEs (UeId=10, 11, 12, 13) in the area which belongs to S-NSSAI = 1 and with active flows of 5QI = 74. • Resource shortage means that minimum bitrate 500 kbps cannot be fulfilled for all users. • E2E Slice assurance function indicates to Non-RT RIC that UeId=10 and 12 needs to be prioritized. • Because of resource shortage, increasing minimum bitrate for UeId=10 and 12 will not improve, instead minimum bitrate for other users in slice needs to be lowered. { { "policy_id": "1", "scope": { "ue_id": "11", "slice_id": "1", "flow_id": "74" }, "statement": { "gfbr": "0" } } { "policy_id": "2", "scope": { "ue_id": "13", "slice_id": "1", "flow_id": "74" }, "statement": { "gfbr": "0" } ETSI ETSI TS 104 226 V10.1.0 (2025-08) 33 } • An alternative way to temporarily change RAN behaviour for S-NSSAI=1 users is to change the relative priority in the scheduler. This would change the relative resource assignment to different users with different priority. - { - { - "policy_id": "1", - "scope": { - "ue_id": "10", - "slice_id": "1", - "flow_id": "74" - }, - "statement": { - "priority_level": "10" - } - } - { - "policy_id": "2", - "scope": { - "ue_id": "12", - "slice_id": "1", - "flow_id": "74" - }, - "statement": { - "priority_level": "10" - } - } - { - "policy_id": "3", - "scope": { - "ue_id": "11", - "slice_id": "1", - "flow_id": "74" - }, - "statement": { - "priority_level": "1" - } - } - { - "policy_id": "4", - "scope": { - "ue_id": "13", - "slice_id": "1", - "flow_id": "74" - }, - "statement": { - "priority_level": "1" - } - } 4.4 Use case 4: Context-based dynamic handover management for V2X
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4.4.0 Introduction
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This use case provides the background, motivation, and requirements for the context-based dynamic HO management for V2X use case, allowing operators to adjust radio resource allocation policies through the O-RAN architecture, reducing latency and improving radio resource utilization. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 34
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4.4.1 Background and goal of the use case
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V2X communication allows for numerous potential benefits such as increasing the overall road safety, reducing emissions, and saving time. Part of the V2X architecture is the V2X UE (SIM + device attached to vehicle) which communicates with the V2X Application Server (V2X AS). The exchanged information comprises Cooperative Awareness Messages (CAMs) (from UE to V2X AS) [i.2], radio cell IDs, connection IDs, and basic radio measurements (RSRP, RSPQ, etc.) As vehicles traverse along a highway, due to their high speed and the heterogeneous natural environment V2X UEs are handed over frequently, at times in a suboptimal way, which can cause handover (HO) anomalies: e.g. short stay, ping- pong, and remote cell. Such suboptimal HO sequences substantially impair the functionality of V2X applications. Since HO sequences are mainly determined by the Neighbour Relation Tables (NRTs), maintained by the xNBs, there is hardly room for UE-level customization. This UC aims to present a method to avoid and/or resolve problematic HO scenarios by using past navigation and radio statistics in order to customize HO sequences on a UE level. To this end, the AI/ML functionality that is enabled by the Near-RT RIC is employed.
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4.4.2 Entities/resources involved in the use case
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1) Non-RT RIC: a) Retrieve necessary performance, configuration, and other data for constructing/training relevant AI/ML models that will be deployed in Near-RT RIC to assist in the V2X HO management function. For example, this could be a clustering algorithm that classifies traffic situations and radio conditions that (probably) do or do not lead to HO anomalies. b) Support deployment and update of AI/ML models into Near-RT RIC xApp. c) Support communication of intents and policies (system-level and UE-level) from Non-RT RIC to Near-RT RIC. d) Support communication of non-RAN data to enrich control functions in Near-RT RIC (enrichment data). 2) Near-RT RIC: a) Support update of AI/ML models retrieved from Non-RT RIC. b) Support interpretation and execution of intents and policies from Non-RT RIC. c) Support necessary performance, configuration, and other data for defining and updating intents and policies for tuning relevant AI/ML models. d) Support communication of configuration parameters to RAN. 3) E2 nodes: a) Support data collection with required granularity to SMO over O1 interface. b) Support near-real-time configuration-based optimization of HO parameters over E2 interface. c) Report necessary performance, configuration, and other data for performing real-time V2X HO optimization in the Near-RT RIC over E2 interface. 4) V2X application server: a) Support data collection with required granularity from V2X UE over V1 interface. b) Support communication of real-time traffic related data about V2X UE to Non-RT RIC as enrichment data. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 35
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4.4.3 Solutions
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4.4.3.1 Context-based dynamic handover management for V2X
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The context of the context-based dynamic handover management for V2X is captured in table 4.4.3.1-1. Table 4.4.3.1-1: Context-based dynamic handover management for V2X Use Case Stage Evolution / Specification <<Uses>> Related use Goal Drive V2X UE HOs in RAN according to defined intents, policies, and configuration while enabling AI/ML-based solutions. Actors and Roles Non-RT RIC: RAN policy control function. Near-RT RIC: RAN policy enforcement function. RAN: Policy enforcement for configuration updates. SMO: Termination point for O1 interface. V2X AS: Termination point for V1 interface and enrichment data provider. Assumptions All relevant functions and components are instantiated. A1, O1, E2 interface connectivity is established. Pre-conditions Network is operational. SMO has established the data collection and sharing process, and Non-RT RIC has access to this data. Non-RT RIC analyses the historical data from RAN and V2X AS for training the relevant AI/ML models to be deployed or updated in the Near-RT RIC, as well as AI/ML models required for real-time optimization of configuration and policies. Begins when Operator specified trigger condition or event is detected. Step 1 (M) Non-RT RIC deploys/updates the AI/ML model in the Near-RT RIC via O1 or Non-RT RIC assigns/update the AI/ML model for the Near-RT RIC xApp via A1. Step 2 (M) Non-RT RIC communicates relevant policies/intents and enrichment data to the Near-RT RIC over the A1 interface. The enrichment data from the non-RAN data can include V2X UE location, trajectory, navigation information, GPS data, CAMs. Step 3 (M) The Near-RT RIC receives the relevant info from the Non-RT RIC over the A1 interface and from the RAN over the E2 interface, interprets the policies and updates the AI/ML models. Step 4 (M) The Near-RT RIC infers optimal RAN configuration (UE-specific NRTs) according to the trained AI/ML models and communicates the result to the RAN over E2 interface. Step 5 (M) RAN deploys the configuration received from the Near-RT RIC over the E2 interface. Step 6 If required, Non-RT RIC can configure specific performance measurement data to be collected from RAN to assess the performance of the V2X HO management function in Near-RT RIC, or to assess the outcome of the applied policies and configuration. Ends when Operator specified trigger condition or event is satisfied. Exceptions None identified. Post Conditions Non-RT RIC monitors the performance of the V2X HO related function in Near- RT RIC by collecting and monitoring the relevant performance KPIs and counters from the RAN and the V2X AS. Traceability • REQ-Non-RT-RIC-FUN1, REQ-Non-RT-RIC-FUN2, REQ-Non-RT- RIC-FUN3, REQ-Non-RT-RIC-FUN4, REQ-Non-RT-RIC-FUN7. • REQ-A1-FUN1, REQ-A1-FUN2, REQ-A1-FUN3, REQ-A1-FUN5. The flow diagram of the V2X HO management use case is given in figure 4.4.3.1-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 36 Figure 4.4.3.1-1: V2X HO management use case flow diagram
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4.4.4 Required data
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The measurement counters and KPIs (as defined by 3GPP) should be appropriately aggregated by cell, QoS type, slice, etc.: 1) Measurement reports with RSRP/RSRQ/CQI information for serving and neighbouring cells. 2) UE connection and mobility/handover statistics with indication of successful and failed handovers and error codes, etc. 3) V2X related data: position, velocity, direction, navigation data, CAMs.
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4.4.5 Proposed solution(s)
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4.4.5.1 Workflow overview
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The use case workflow consists of these main components: 1) Data collection & maintenance: This is required at Non-RT RIC (over O1 and Enrichment Interface (EI)). Required radio measurements and V2X related metrics are collected over a longer period of time (sufficient to facilitate model training). The O1/EI data collection is used for offline training of models, as well as for generating A1 policies for V2X HO optimization. The E2 (and EI) data collection is used for model execution in the Near-RT RIC. Details of the models are described below. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 37 2) Long-term HO analytics & model maintenance: The Non-RT RIC long-term analytics is responsible for providing the relevant models for V2X HO optimization over A1 interface. Based on O-RAN A1 interface specs v1, these policies can be defined at per-UE level, UE group level, cell or xNB level, etc. This will provide the optimization scope/objective for the Near-RT RIC V2X HO xApp. The xApp hosts two AI/ML- assisted functions: 1. HO anomaly detection & prediction, 2. HO anomaly avoidance. The 1. trained model's input is [E2: HO sequences, UE radio measurements; EI: position, velocity, direction, (O) navigation data, (O) cell load data of cells in the area] of a given time window, while the output is [anomaly likelihoods for possible future HO sequences]. The 2. trained model's input is [E2 report, EI report, output of 1. model, (O) navigation data, (O) cell load data of cells in the area] and its output is [UE-customized NRT sequence for cells that the UE is about to touch, with lower anomaly likelihood, (O) with validity time]. The two models are regularly retrained/updated based on new radio/V2X data. 3) HO anomaly prediction & detection: The navigation information and HO sequence and predicted HO sequence of V2X UEs in scope are evaluated and HO anomalies are detected or predicted. If any, it is delegated for further consideration for HO sequence optimization. 4) HO sequence optimization: Based on the E2 and enrichment reports and the prediction/detection output, the trained AI/ML model outputs UE-customized NRTs for the cells that I. are in scope, II. the UE is about to come in touch with. 5) V2X HO optimization execution: The new NRTs are deployed at xNBs through E2 policies.
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4.4.5.2 Overview of ML models
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While many combinations and deployments are possible, this proposal outlines one specific set of models and analytics that can be useful to drive such a use case. NonRT_Model1: The Non-RT RIC ML-assisted solution uses the O1-based and EI-based data collection to monitor the V2X UE HO performance metrics and the navigation indicators (position, direction, speed, (O) traffic indicators). Based on the performance monitoring, the model aims to represent navigation and radio environments/conditions and maintain a data base in order to classify HO situations. Input: historical radio, HO, and location, direction, velocity data. Output: maintained database with locations, directions, velocities and cells, HO situations, HO anomalies, and/or sequences of all these, together with prevalence rates (=estimated probabilities). NearRT_Model1: The first ML-assisted near-RT xApp model in the Near-RT RIC aims to rate/score future/current HO situations (on a UE level) based on real-time radio (E2) and navigation conditions (EI), i.e. predict/detect anomalous HO situations. Input: per-UE current radio parameters, HO history, location, direction, velocity. Output: predicted HO sequence(s) with probabilities for anomalies at specific cell pairs. NearRT_Model2: The second ML-assisted near-RT xApp model in the Near-RT RIC aims to choose alternative, UE specific NRTs for a set of cells and UEs so as to resolve or avoid anomalous HO situations. Input: input and output of the NearRT_Model1. Output: alternative, UE specific NRTs for some cells (e.g. with temporal validity/expiration time).
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4.4.6 A1 enrichment interface aspects
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1) As per ETSI EN 302 637-2 [i.2], V2X UE provides CAMs (which include its GPS coordinates) on a 0.1-1s temporal granularity to the V2X application server. The inference part of this use case depends on accurate navigation data from V2X UEs, thus O-RAN expects this data to be provided through the A1-EI without substantial processing or delay. 2) The data (in particular the GPS coordinates) received over A1-EI need to be correlated with RAN UE data. For this problem there might be different requirements for the training data collection and the inference data collection. E.g. the UE data association might be solved using the ECGI + C-RNTI identifiers at any point in time (inference), but when collecting historical data for training it is essential to save the data in such a way that later correlation is possible as well. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 38
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4.4.7 A1 usage example
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As of now the A1 aspect of the use case is confined to whether the HO optimization is, within a certain scope, activated or not. Thus, some of the attributes can overlap with the policy scope, but they are proposed in order to allow for more fine-grained control (e.g. optimize for only vehicles that are faster than 100 km/h [vel_range], between 7 am and 9 am on workdays [time_range], within a given geographical area [pos range] or [cell_id_list].) The proposed (optional) attributes of the statement type v2x_nrt_opt are captured in table 4.4.7-1. Table 4.4.7-1: Definition of statement type v2x_nrt_opt/extra scope identifiers Attribute name Data type P Cardinality Description Applicability cell_id_list Array "M" "1..N" list of CellIDs time_range Array "O" "1..N" refers to the time intervals of activation pos_range Array "O" "1..N" refers to GPS position ranges of activation vel_range Array "O" "1..N" refers to velocity ranges of activation { "title": "policies", "description": "O-RAN A1 policy", "type": "object", "properties": { "policy_id": {"type": "string"}, "scope": { … }, "statement": { "cell_id_list": {"type": "number"}, "time_range": {"type": "number"}, " pos_range": {"type": "number"}, " vel_range": {"type": "number"} } } } ETSI ETSI TS 104 226 V10.1.0 (2025-08) 39
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4.5 Use case 5: RAN slice SLA assurance
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4.5.0 Introduction
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The 3GPP standards architected a sliceable 5G infrastructure which allows creation and management of customized networks to meet specific service requirements that can be demanded by future applications, services and business verticals. Such a flexible architecture needs different requirements to be specified in terms of functionality, performance and group of users which can greatly vary from one service to the other. The 5G standardization efforts have gone into defining specific slices and their Service Level Agreements (SLAs) based on application/service type as specified in 3GPP TS 23.501 [2]. Since network slicing is conceived to be an end-to-end feature that includes the core network, the transport network and the Radio Access Network (RAN), these requirements should be met at any slice subnet during the life-time of a network slice as specified in 3GPP TS 28.530 [3], especially in RAN side. Exemplary slice performance requirements are specified in terms of throughput, energy efficiency, latency and reliability at a high level in SDOs such as 3GPP TS 22.261 [1] and GSMA [9]. These requirements are defined as a reference for SLA/contractual agreements for each slice, which individually need proper handling in NG-RAN. Although network slicing support is started to be defined with 3GPP Release 15, slice assurance mechanisms in RAN needs to be further addressed to achieve deployable network slicing in an open RAN environment. It is necessary to assure the SLAs by dynamically controlling slice configurations based on slice specific performance information. Existing RAN performance measurements as specified in 3GPP TS 28.552 [5] and information model definitions as specified in 3GPP TS 28.541 [4] are not enough to support RAN slice SLA assurance use cases. This use case is intended to clarify necessary mechanisms and parameters for RAN slice SLA assurance.
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4.5.1 Background and goal of the use case
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In the 5G era, network slicing is a prominent feature which provides end-to-end connectivity and data processing tailored to specific business requirements. These requirements include customizable network capabilities such as the support of very high data rates, traffic densities, service availability and very low latency. According to 5G standardization efforts, the 5G system can support the needs of the business through the specification of several service needs such as data rate, traffic capacity, user density, latency, reliability, and availability. These capabilities are always provided based on a Service Level Agreement (SLA) between the mobile operator and the business customer, which brought up interest for mechanisms to ensure slice SLAs and prevent its possible violations. O-RAN's open interfaces and AI/ML based architecture will enable such challenging mechanisms to be implemented and help pave the way for operators to realize the opportunities of network slicing in an efficient manner.
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4.5.2 Entities/resources involved in the use case
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1) Non-RT RIC: a) Retrieve RAN slice SLA target from respective entities such as SMO, NSSMF. b) Long term monitoring of RAN slice performance measurements. c) Training of potential ML models that will be deployed in Non-RT RIC for slow loop optimization and/or Near-RT RIC for fast loop optimization. d) Support deployment and update of AI/ML models into Near-RT RIC. e) Receive slice control/slice SLA assurance rApps from SMO. f) Create and update A1 policies based on RAN intent and A1 feedback. g) Send A1 policies and enrichment information to Near-RT RIC to drive slice assurance. h) Send O1 reconfiguration requests to SMO for slow-loop slice assurance. 2) Near-RT RIC: a) Near-real-time monitoring of slice specific RAN performance measurements. b) Support deployment and execution of the AI/ML models from Non-RT RIC. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 40 c) Receive slice SLA assurance xApps from SMO. d) Support interpretation and execution of policies from Non-RT RIC. e) Perform optimized RAN (E2) actions to achieve RAN slice requirements based on O1 configuration, A1 policy, and E2 reports. 3) E2 nodes: a) Support slice assurance actions such as slice-aware resource allocation, prioritization, etc. b) Support slice specific performance measurements through O1. c) Support slice specific performance reports through E2.
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4.5.3 Solutions
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4.5.3.1 Creation and deployment of RAN slice SLA assurance applications
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The context of the creation and deployment of RAN slice SLA assurance applications is captured in table 4.5.3.1-1. Table 4.5.3.1-1: Creation and deployment of RAN slice SLA assurance applications Use Case Stage Evolution / Specification <<Uses>> Related use Goal Training and distribution of the RAN slice SLA assurance applications. Actors and Roles Non-RT RIC, Near-RT RIC, SMO Assumptions All relevant functions and components are instantiated. A1, O1 interface connectivity is established. Pre-conditions Near-RT RIC and Non-RT RIC are instantiated with A1 interface. A1 connectivity being established between them. O1 interface is established between SMO and Near-RT RIC. Begins when A RAN slice is activated, or an operator defined trigger is detected. Step 1 (M) Non-RT RIC retrieves a RAN slice SLA from SMO (e.g. from NSSMF). Step 2a (O) Non-RT RIC starts to collect slice specific performance measurements (PMs) via O1. Examples of the PMs are CSI, PRB usage, L2 throughput, RAN latency, etc. Applicable PMs are specified in 3GPP TS 28.552 [5]. Step 2b (O) Non-RT RIC starts to collect Enrichment Information (EIs) from external applications. Examples of the external applications are public safety application triggering slice priority during an emergency event, or location- based enrichment information, etc. Step 3 (O) Non-RT RIC does the model training during a certain period of time using the collected data in step 2 and generates RAN slice SLA assurance AI/ML models. Step 4 (M) Non-RT RIC deploys RAN slice SLA assurance rApp (which can include the newly trained AI/ML model(s)). Step 5 (O) Non-RT RIC deploys RAN slice SLA assurance xApp(s) to respective Near- RT RICs (which can include the newly trained AI/ML model(s)). Step 6 (O) Non-RT RIC continues collecting slice specific performance measurements (PMs) via O1 and receives/utilizes A1 feedback if available. Non-RT RIC can update the AI/ML models within rApp and xApp(s). Ends when A RAN slice is deactivated. Exceptions None identified. Post Conditions RAN slice SLA assurance applications are deployed. Traceability REQ-Non-RT-RIC-FUN1, REQ-Non-RT-RIC-FUN2, REQ-Non-RT-RIC- FUN3, REQ-Non-RT-RIC-FUN4, REQ-Non-RT-RIC-FUN5, REQ-Non-RT- RIC-FUN9, REQ-A1-FUN2, REQ-A1-FUN4 The flow diagram of the creation and deployment of RAN slice SLA assurance applications is given in figure 4.5.3.1-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 41 Figure 4.5.3.1-1: Creation and deployment of RAN slice SLA assurance applications
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4.5.3.2 RAN slice SLA assurance
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The context of RAN slice SLA assurance is captured in table 4.5.3.2-1. Table 4.5.3.2-1: RAN slice SLA assurance Use Case Stage Evolution / Specification <<Uses>> Related use Goal RAN slice SLA assurance Actors and Roles SMO functions, Non-RT RIC framework, RAN slice SLA assurance rApp, Near-RT RIC, E2 nodes Assumptions All relevant functions and components are instantiated. A1, O1, E2 interface connectivity is established. Pre-conditions Near-RT RIC and Non-RT RIC are instantiated with A1 interface connectivity being established between them. O1 interfaces are established between SMO and Near-RT RIC, and SMO and E2 nodes. RAN slice SLA assurance applications have been deployed in Non-RT RIC and Near-RT RIC respectively. Begins when A RAN slice is activated, or an operator defined trigger is detected. Step 1 (M) RAN slice SLA assurance rApp retrieves relevant information from Non-RT RIC framework via R1, such as active RAN slices (such as active S- NSSAIs, network slice subnet instances, topology), RAN slice SLA information, NF configuration, etc. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 42 Use Case Stage Evolution / Specification <<Uses>> Related use Step 2 (O) RAN slice SLA assurance rApp retrieves relevant enrichment information from Non-RT RIC framework via R1. Step 3a (M) RAN slice SLA assurance rApp requests relevant slicing specific PMs. Examples of the PMs are layer 2 throughput, PRB usage, CSI, RAN latency. Step 3b (M) Non-RT RIC framework triggers retrieval of requested O1 PMs by interacting with SMO. Step 3c (M) RAN slice SLA assurance rApp starts retrieving E2 node generated slice specific PMs from Non-RT RIC framework via R1. Step 4 (M) RAN slice SLA assurance rApp monitors and evaluates performance of RAN slices which can include detection of possible RAN slice SLA violation. Step 5 (O) RAN slice SLA assurance rApp decides to apply O1 reconfiguration on certain E2 nodes and/or Near-RT RIC. RAN slice SLA assurance rApp triggers O1 reconfiguration through Non-RT RIC framework using R1. Step 6a (O) RAN slice SLA assurance rApp decides to apply A1 policy based RAN slice SLA assurance considering RAN slice SLA requirements and/or operator- defined RAN intents, EI from external application servers and O1 based long term trends. In addition to these input parameters, A1 feedback from Near-RT RIC, when available, can be utilized for updating existing policies. The policies include scope identifiers (e.g. S-NSSAI, flow ID, and cell ID) and/or policy statements (e.g. slice specific KPI targets). Step 6b (O) RAN slice SLA assurance rApp triggers creation/update/removal of A1 policies on respective Near-RT RICs through Non-RT RIC framework via R1. Step 6c (O) Non-RT RIC framework applies A1 policy creation/update/removal on respective Near-RT RICs through A1 interface. Step 6d (O) Near-RT RIC applies A1 policy-based RAN slice SLA assurance. Step 6e (O) RAN slice SLA assurance rApp retrieves A1 feedback generated from respective Near-RT RICs. Steps include Near-RT RIC sending the A1 feedback via A1 to Non-RT RIC framework, and then rApp retrieving this feedback via R1 from Non-RT RIC framework. Ends when RAN slice(s) is deactivated or an operator defined trigger is detected. Exceptions None identified. Post Conditions SLA assurance for RAN slice(s) over a period of time is achieved. Traceability REQ-Non-RT-RIC-FUN1, REQ-Non-RT-RIC-FUN5, REQ-Non-RT-RIC- FUN8, REQ-Non-RT-RIC-FUN9, REQ-A1-FUN1, REQ-A1-FUN3, REQ-A1- FUN5 The flow diagram of the RAN slice SLA assurance is given in figure 4.5.3.2-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 43 Figure 4.5.3.2-1: RAN slice SLA assurance
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4.5.4 Required data
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The measurement counters and KPIs (as defined by 3GPP and will be extended for O-RAN use cases) should be appropriately aggregated by cell, QoS type, slice, etc. Examples for required data for RAN slice SLA assurance use case are as follows: 1) Per UE and/or per slice performance statistics as specified in 3GPP TS 28.552 [5], 3GPP TS 36.314 [6], 3GPP TS 38.314 [7] such as: a) CQI related measurements; such as wideband CQI distribution (as specified in 3GPP TS 28.552 [5], clause 5.1.1.11.1), per-UE CQI measurements (including supported S-NSSAIs of the UE) [Definition needed] b) UE throughput related measurements; such as average DL / UL UE throughput in gNB (as specified in 3GPP TS 28.552 [5], clauses 5.1.1.3.1, 5.1.1.3.3), scheduled IP throughput in DL/UL (as specified in 3GPP TS 36.314 [6], clause 4.1.6.1) c) RRC connection related measurements; such as mean / max number of RRC connections (as specified in 3GPP TS 28.552 [5], clauses 5.1.1.4.1, 5.1.1.4.2), attempted / successful RRC connection establishments (as specified in 3GPP TS 28.552 [5], clauses 5.1.1.15.1, 5.1.1.15.2) d) DRB related measurements; such as number of DRBs attempted to / successfully setup (as specified in 3GPP TS 28.552 [5], clauses 5.1.1.10.1, 5.1.1.10.2) ETSI ETSI TS 104 226 V10.1.0 (2025-08) 44 e) PDU session management related measurements; such as number of PDU sessions requested to / successfully / failed to setup (as specified in 3GPP TS 28.552 [5], clauses 5.1.1.5.1, 5.1.1.5.2, 5.1.1.5.3) f) Number of active UEs; such as number of active UEs in the UL / DL per cell (as specified in 3GPP TS 28.552 [5], clauses 5.1.1.23.1, 5.1.1.23.3) g) Radio resource utilization related measurements; such as DL / UL PRB used for data traffic (as specified in 3GPP TS 28.552 [5], clauses 5.1.1.2.5, 5.1.1.2.7) h) PDCP data volume measurements; such as DL / UL PDCP PDU data volume (as specified in 3GPP TS 28.552 [5], clauses 5.1.3.6.1.1, 5.1.3.6.1.2), data volume in DL/UL (as specified in 3GPP TS 36.314 [6], clauses 4.1.8.1, 4.1.8.2) i) Average user plane delay; such as PDCP queuing delay in UE [Definition needed], average delay DL air- interface (as specified in 3GPP TS 28.552 [5], clause 5.1.1.1.1), average delay UL on over-the-air interface (as specified in 3GPP TS 28.552 [5], clause 5.1.1.1.3), average delay DL in gNB-DU (as specified in 3GPP TS 28.552 [5], clause 5.1.3.3.3), average delay DL on F1-U (as specified in 3GPP TS 28.552 [5], clause 5.1.3.3.2), average delay DL in CU-UP (as specified in 3GPP TS 28.552 [5], clause 5.1.3.3.1), average over-the-air interface packet delay in the DL / UL per DRB per UE (as specified in 3GPP TS 38.314 [7], clause 4.2.1.2.2), average delay DL air-interface (as specified in 3GPP TS 28.558 [21], clause 6.3.1.1.1) j) Packet drop and loss rate measurements; such as DL packet drop rate in gNB-DU (as specified in 3GPP TS 28.552 [5], clause 5.1.3.2.2), UL / DL F1-U packet loss rate (as specified in 3GPP TS 28.552 [5], clauses 5.1.3.1.2, 5.1.3.1.3), packet Uu loss rate in the DL per DRB per UE (as specified in 3GPP TS 38.314 [7], clause 4.2.1.5.1) 2) O1 configuration information for NR NRM such as NRCellCU (as specified in 3GPP TS 28.541 [4], clause 4.3.4), NRCellDU (as specified in 3GPP TS 28.541 [4], clause 4.3.5), GNBDUFunction (as specified in 3GPP TS 28.541 [4], clause 4.3.1), GNBCUCPFunction (as specified in 3GPP TS 28.541 [4], clause 4.3.2), GNBCUUPFunction (as specified in 3GPP TS 28.541 [4], clause 4.3.3), RRMPolicy (as specified in 3GPP TS 28.541 [4], clause 4.3.43) 3) Slice SLA information; such as ServiceProfile (as specified in 3GPP TS 28.541 [4], clause 6.3.3), SliceProfile (as specified in 3GPP TS 28.541 [4], clause 6.3.4) 4) Enrichment information; such as UE geo-location information (as specified in A1TD [22], clause 8.3.3.2)
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4.5.5 A1 usage example
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Example scenario 1 • One mobile leased line network slice for live broadcasting is defined (S-NSSAI=1). • The SLA for the slice is defined with the total UL/DL throughput of 30 Mbps of the users in the slice provided in the coverage area (cellId=1, 2, 3). • Non-RT RIC generates A1 policy for Near-RT RIC slice SLA assurance, which includes S-NSSAI and cellId as scope identifiers, and per-slice total PDCP layer throughput target as a policy statement. • Near-RT RIC enforces the policy and guides RAN behaviour via E2 to meet the slice SLA. { "PolicyId": "1", "scope": { "sliceId": "1", "cellId": "1", "2", "3", // Multiple cellIds need to be supported }, "statement": { "uLThptPerSlice": "30" ETSI ETSI TS 104 226 V10.1.0 (2025-08) 45 "dLThptPerSlice": "30" } } Example scenario 2 Background of the scenario: • SLA violation occurs when a cell is congested, and not enough resources are allocated to slice users. To minimize this kind of SLA violation, load balancing is effective. • Although load balancing can be performed using traffic steering preference policy type, that approach is insufficient to reduce the load to desired level, because there will be a gap between the actual load and the load recognized by Non-RT RIC due to long monitoring and control interval of Non-RT RIC. As shown in figure 4.5.5-1, the near-real-time control loop can achieve smaller reaction time than the non-real-time control loop. Therefore, it is preferable to use Near-RIC for load balancing. • In this scenario, by using A1 policy for load balancing, the load balancing is performed in a shorter cycle, which is more effective in assuring slice SLAs. Figure 4.5.5-1: Illustration of the control loops involving Non-RT RIC, Near-RT RIC and E2 nodes Overall flow in the scenario: • In this scenario, Non-RT RIC monitors the load and performance under the cell and decides whether the cell load should be balanced or not. Only when cell congestion is detected or predicted, A1 policy for load balancing is sent to Near-RT RIC, and Near-RT RIC performs cell load balancing to ease the cell congestion and solve SLA violation. • The following example describes the overall steps in load balancing to assure slice SLAs defined by delay requirement. Note that the step number corresponds to the number given in figure 4.5.5-2. 1) An A1 policy (PolicyId: 1) corresponding to SLA of slice #1, which includes delay requirement per UE for users of cell A~E, and slice #1, is sent from Non-RT RIC to Near-RT RIC. 2) To monitor the cell load and performance of delay, Non-RT RIC collects mean DL PRB used for data traffic (as specified in 3GPP TS 28.552 [5], clause 5.1.1.2.5) from cell A~E, and distribution of delay DL air-interface (per S-NSSAI) (as specified in 3GPP TS 28.552 [5], clause 5.1.1.2.2) from cell A~E via O1. 3) In Non-RT RIC, when the load of cell A is high, and the percentage of packets of slice #1 experiencing a longer delay than required, Non-RT RIC determines that the SLA violation is due to high load and decides to start load balancing. Non-RT RIC sends an A1 policy (PolicyId: 2) to transfer the load of cell A to neighbouring non-congested cells (cell B, D and E) until the load of cell A becomes smaller than 80 %. 4) To monitor the load and radio quality, Near-RT RIC collects mean DL PRB used for data traffic (as specified in 3GPP TS 28.552 [5], clause 5.1.1.2.5) from cell A~E, and per-UE RSRP measurement and RSRQ measurement (as specified in O-RAN.WG3.E2SM-KPM [16], clauses 8.2.1.2.2, 8.2.1.2.3 and in 3GPP TS 28.552 [5], clauses 5.1.1.22, 5.1.1.31) via E2. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 46 5) Near-RT RIC decides the combination of UEs to be handed over and target cells based on the information collected in (4). Near-RT RIC sends E2 CONTROL for UE-level hand over control to decrease the load of cell A below 80 %. 6) Non-RT RIC continues to monitor the cell load and performance. When Non-RT RIC decides that the cell load becomes low enough to not cause SLA violation, it notifies deletion of the policy (PolicyId: 2) to Near-RT RIC. Figure 4.5.5-2: Illustration of the overall flow in the load balancing scenario { "PolicyId": "2", "scope": { "cellId": "A" // Designate a cell of which load is to be transferred to other cells }, "lbObjectives": { "targetPrbUsg": 80 // Target load of Cell A "prbUsgType": 1 // PRB usage type used in the calculation of targetPrbUsg }, "lbResources": { "cellIdList": "B", "D", "E", // Designate cells to which cell load is transferred } } The illustration of the cell congestion in multi-cell environment is given in figure 4.5.5-3. Figure 4.5.5-3: Illustration of the cell congestion in multi-cell environment ETSI ETSI TS 104 226 V10.1.0 (2025-08) 47
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4.5.6 O1 usage example
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Example scenario • One mobile leased line network slice for live broadcasting is defined (S-NSSAI=1). • The SLA for the slice is defined with the average total UL/DL throughput of 30 Mbps of the users in the slice provided in the coverage area (cellId=1, 2, 3). • Note that O1 configuration is used to assure SLAs defined as long term performance values such as average throughput, which do not need frequent reconfiguration. • In order to calculate the number of required PRBs to meet throughput requirement of the slice, Non-RT RIC collects wideband CQI distribution and data volume in UL/DL via O1. The calculated value is converted to the portion of PRB allocation to the slice i.e. rRMPolicyDedicatedRatio (as specified in 3GPP TS 28.541 [4]). • Non-RT RIC sends rRMPolicyDedicatedRatio as O1 reconfiguration requests to E2 nodes. • Non-RT RIC also collects UL/DL PRB used for data traffic and average UL/DL UE throughput in gNB. When the PRB usage becomes low, Non-RT RIC reconfigures rRMPolicyDedicatedRatio via O1 to decrease the allocated PRBs. When the PRB usage becomes high and throughput deterioration occurs, Non-RT RIC reconfigures rRMPolicyDedicatedRatio via O1 to increase the allocated PRBs. The illustration of the RRMPolicy reconfiguration via O1 is given in figure 4.5.6-1. Figure 4.5.6-1: Illustration of the RRMPolicy reconfiguration via O1
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4.6 Use case 6: NSSI resource optimization
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4.6.0 Introduction
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This use case provides the background, objectives, solution, and requirements for the NSSI resource optimization, an rApp implemented in Non-RT RIC, which leverages AI/ML inference on slice performance measurement data to determine the actions to automatically optimize the resource allocation for network slice instances.
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4.6.1 Background and goal of the use case
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Network slicing is essential to 5G, as it enables many new services across manufacturing, autonomous driving, gaming, and many more via the provision of ultra-low latency in URLLC and huge data volume in eMBB features that require different or contrasting QoS requirements exploiting a shared RAN node. The goal of this use case is to ensure the resources are allocated dynamically and efficiently among multiple network slices sharing the RAN node. Time PRB usage Slice #1 Allocated PRB For slice #1 (S-NSSAI=1) Slice #n Time PRB usage Slice #1 Allocated PRB For slice #1 (S-NSSAI=1) Slice #n Decrease PRBs for Slice #1 via O1 (rRMPolicyRatio) Increase PRBs for Slice #1 via O1 (rRMPolicyRatio) Time PRB usage Slice #1 Allocated PRB For slice #1 (S-NSSAI=1) Slice #n Monitoring and Reconfiguration in Non-RT RIC Initial portion is calculated with “Wideband CQI distribution” and “Data volume in UL” Throughput deterioration Low PRB usage High PRB usage ETSI ETSI TS 104 226 V10.1.0 (2025-08) 48 As the new 5G services have different characteristics, the network traffic tends to be sporadic, where there can be different usage pattern in terms of time, location, UE distribution, and types of applications. For example, most IoT sensor applications can run during off-peak hours or weekends. Special events, such as sport games, concerts, can cause traffic demand to shoot up at certain time and locations. Cars with autonomous driving capability tend to require more URLLC services in the morning or afternoon rush hours in major freeways in big cities, while subscribers tend to consume eMBB services to watch video streaming at night in residential areas. Therefore, NSSI resource optimization rApp trains the AI/ML model, based on the huge volume of performance data collected over days, weeks, months from O-RAN nodes. It then performs inference function on the model with input measurements to predict the traffic demand patterns of 5G networks in different times and locations for each network slice, and automatically optimize the resource allocation for network slice instances accordingly.
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4.6.2 Entities/resources involved in the use case
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1) Non-RT RIC: a) Receive measurements to monitor the usage of RRM resources (e.g. PRB, RRC, DRB) identified by S-NSSAI from E2 nodes via the O1 interface. b) Perform the model training with input measurements data received from E2 nodes to create the model. c) Perform the inference function on the model with the input measurements data to determine if any actions shall be executed to update the resources on the E2 nodes. d) Configure the resources at the E2 nodes via O1 interface. e) Receive notifications from E2 nodes indicating the resource re-configuration was done. f) Update the O-Cloud resources via the O2 interface. g) Receive notifications from O-Cloud indicating the resource was updated. 2) E2 nodes (O-CU-CP, O-CU-UP, D-DU): a) Support the collections and reporting of measurements that are used to monitor the resource usage on per network slice basis via the O1 interface. b) Support the re-configuration of attributes to update the resources allocated to each network slice via the O1 interface.
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4.6.3 Solutions
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4.6.3.1 NSSI resource optimization
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The context of the NSSI resource optimization is captured in table 4.6.3.1-1. Table 4.6.3.1-1: NSSI resource optimization Use Case Stage Evolution / Specification <<Uses>> Related use Goal The goal is to ensure the resources (e.g. PRB, RRC, DRB) are allocated dynamically and efficiently among multiple network slices sharing the E2 nodes. Actors and Roles • SMO functions. • Non-RT RIC framework. • rApp: NSSI resource optimization. • E2 nodes (i.e. O-CU-CP, O-CU-UP, O-DU). Assumptions • All relevant functions and components are instantiated. • O1 interface connectivity is established. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 49 Use Case Stage Evolution / Specification <<Uses>> Related use Pre-conditions • O1 interfaces have been established to enable SMO to receive measurements from E2 nodes and configure the E2 nodes. • R1 interface has been established to enable the rApp to receive measurements form E2 nodes and configure the E2 nodes via Non-RT RIC framework. • E2 nodes have been configured to collect the measurements and send them to Non-RT RIC framework. Begins when The rApp utilizes the model to perform the inference function. Step 1 (M) The rApp performs the offline model training with input measurements data received from E2 nodes to create the model. Step 2 (M) Non-RT RIC framework receives the measurements from O-CU-CP via O1 to monitor the usage of RRM resources (e.g. RRC connected user). Step 3 (M) Non-RT RIC framework sends the measurements to rApp via R1 interface. Step 4 (M) Non-RT RIC framework receives the measurements from O-CU-UP via O1 to monitor the usage of RRM resources (e.g. the number of DRB allocated, and the number of PDU sessions). Step 5 (M) Non-RT RIC framework sends the measurements to rApp via R1 interface. Step 6 (M) Non-RT RIC framework receives the measurements from O-CU-UP via O1 to monitor the usage of RRM resources (e.g. the number of PRBs used in the downlink and uplink data traffic). Step 7 (M) Non-RT RIC framework sends the measurements to rApp via R1 interface. Step 8 (M) The rApp performs the inference function based on the model with input measurements data received to determine the actions to update the resources allocated to slices on the E2 nodes if needed. If the rApp decides the RRM resources (e.g. RRC) in O-CU-CP need to be updated, then steps 9 to 12 are executed. Step 9 (O) rApp requests Non-RT RIC framework via R1 interface to update the RRM resources for slices in O-CU-CP. Step 10 (O) Non-RT RIC framework uses the modify MOI (Managed Object Instance) operation to configure the MOI(s) associated with the RRM resources at O- CU-CP via O1 interface. Step 11 (O) Non-RT RIC framework receives a notification from O-CU-CP via O1 interface indicating the resource re-configuration was successful. Step 12 (O) Non-RT RIC framework notifies rApp via R1 interface indicating the RRM resources in O-CU-CP have been successfully updated. If the rApp decides the RRM resources (e.g. DRB) in O-CU-UP need to be updated, then steps 13 to 16 are executed. Step 13 (O) rApp requests Non-RT RIC framework via R1 interface to update the RRM resources for slices in O-CU-UP. Step 14 (O) Non-RT RIC framework uses the modify MOI operation to configure the MOI(s) associated with the RRM resource at O-CU-UP via O1 interface. Step 15 (O) Non-RT RIC framework receives a notification from O-CU-UP via O1 interface indicating the resource re-configuration was successful. Step 16 (O) Non-RT RIC framework notifies rApp via R1 interface indicating the RRM resources in O-CU-UP have been successfully updated. If the rApp decides the RRM resources (e.g. PRB) in O-DU need to be updated, then steps 17 to 20 are executed. Step 17 (O) rApp requests Non-RT RIC framework via R1 interface to update the RRM resources for slices in O-DU. Step 18 (O) Non-RT RIC framework uses the modify MOI operation to configure the MOI(s) associated with the RRM resource at O-DU via O1 interface. Step 19 (O) Non-RT RIC framework receives a notification from O-DU via O1 interface indicating the resource re-configuration was successful. Step 20 (O) Non-RT RIC framework notifies rApp via R1 interface indicating the RRM resources in O-DU have been successfully updated. If the rApp decides the O-Cloud resources need to be updated, then steps 21 to 24 are executed: Step 21 (O) rApp requests Non-RT RIC framework via R1 interface to update the O-Cloud resources. Step 22 (O) Non-RT RIC framework re-configures the O-Cloud resources via O2 interface. Step 23 (O) Non-RT RIC framework receives a notification via O2 interface indicating the resource re-configuration was successful. Step 24 (O) Non-RT RIC framework notifies rApp via R1 interface indicating the O-Cloud resources have been successfully updated. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 50 Use Case Stage Evolution / Specification <<Uses>> Related use Ends when The resources have been optimized. Exceptions None identified. Post Conditions None. Traceability REQ-R1-FUN9, REQ-R1-FUN10. NOTE: How the O-Cloud resources are to be monitored and updated is not defined in the present document. The flow diagram of the NSSI resource optimization is given in figure 4.6.3.1-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 51 Figure 4.6.3.1-1: NSSI resource optimization flow diagram ETSI ETSI TS 104 226 V10.1.0 (2025-08) 52
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4.6.4 Required data
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4.6.4.0 Introduction
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This clause contains the input and output data of model training and inference.
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4.6.4.1 Input data
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The measurement input data are used in model training and inference. They include the following measurements to monitor the resource usage for network slices in E2 nodes: 1) Measurements used to monitor the usage of RRC related resources in O-CU-CP include: - Mean number of RRC connections - provides the mean number of RRC connections with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.4.1). - Peak number of RRC connections - provides the peak number of RRC connections with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.4.2). 2) Measurements used to monitor the usage of DRB related resources in O-CU-UP include: - Mean number of DRBs being allocated - provides the mean number of DRBs being allocated in the PDU sessions with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.10.10). - Peak number of DRBs being allocated - provides the peak number of DRBs being allocated in the PDU sessions with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.10.9). 3) Measurements used to monitor the usage of PRB related resources in O-DU include: - Mean DL PRB used for data traffic - provides the mean number of PRBs used in downlink for data traffic with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.2.5). - Peak DL PRB used for data traffic - provides the peak number of PRBs used in downlink for data traffic with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.2.9). - Mean UL PRB used for data traffic – provides the mean number of PRBs used in uplink for data traffic with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.2.7). - Peak UL PRB used for data traffic - provides the peak number of PRBs used in uplink for data traffic with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.2.10). - Mean number of PDU sessions being allocated - provides the mean number of PDU sessions being allocated with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.5.4). - Peak number of PDU sessions being allocated - provides the peak number of PDU sessions being allocated with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.5.5). - Mean number of active UEs in the DL per cell - provides the mean number of active UEs in downlink with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.23.1). - Maximum number of active UEs in the DL per cell - provides the maximum number of active UEs in downlink with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.23.2). - Mean number of active UEs in the UL per cell - provides the mean number of active UEs in uplink with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.23.3). - Maximum number of active UEs in the UL per cell - provides the maximum number of active UEs in uplink with sub-counters per S-NSSAI (as specified in 3GPP TS 28.552 [5], clause 5.1.1.23.4). ETSI ETSI TS 104 226 V10.1.0 (2025-08) 53
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4.6.4.2 Output data
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The output data, including NRCellCU IOC, NRCellDU IOC, GNBDUFunction IOC, GNBCUCPFunction IOC, GNBCUUPFunction IOC and RRMPolicyRatio IOC with RRMPolicy abstract class (as specified in 3GPP TS 28.541 [4]), are needed to enable NSSI resource optimization rApp to re-configure the resources via O1 and O2 interfaces.
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104 226
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4.6.5 O1 usage example
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An example of two NSSIs, where NSSI#1 groups E2 nodes (i.e. O-DU, O-CU-CP, and O-CU-UP), and NSSI#2 groups 5GC NFs is shown in figure 4.6.5-1. It also shows that two network slices, identified by S-NSSAI#1 supporting URLLC, and S-NSSAI#2 supporting eMBB. The goal of this use case is to optimize the resources associated with RAN network slices. O-DU O-CU-UP O-CU-CP 5GC S-NSSAI#1 S-NSSAI#2 S-NSSAI#1 S-NSSAI#1 S-NSSAI#2 S-NSSAI#2 NSSI#1 NSSI#2 Control plane User plane Figure 4.6.5-1: NSSI resource optimization example NSSI resources optimization rApp runs model inference with input measurement data collected from E2 nodes for S-NSSAI#1 and S-NSSAI#2, and detects a traffic pattern for O-DU serving an area with high density of business and residential users at the time on a given day. An example of PRB resource allocation for S-NSSAI#1 and S-NSSAI#2 at the O-DU is shown in figure 4.6.5-2: • At 15:00, the dedicated resources and prioritized resources for S-NSSAI#1 were increased to 20 % and 50 % respectively for as more cars demand more URLLC services at the start of rush hours. • At 17:00, the dedicated resources, prioritized resources, and shared resources for S-NSSAI#1 were further increased as the rush hours traffic getting worse. • At 19:00, the dedicated resources, prioritized resources, and shared resources for S-NSSAI#2 were increased to 20 %, 60 %, and 75 % respectively as more residential users demand more eMBB services for home video streaming. • At 20:00, the dedicated resources, prioritized resources, and shared resources for S-NSSAI#1 were decreased as the rush hours traffic coming to end. • At 21:00, the dedicated resources, prioritized resources, and shared resources for S-NSSAI#2 were further increased as the demand for eMBB services increased. • At 22:00, the dedicated resources, prioritized resources, and shared resources for S-NSSAI#1were decreased as the demand for URLLC services further reduced. • At 24:00, the dedicated resources, prioritized resources, and shared resources for S-NSSAI#2 were decreased to 10 %, 25 %, and 60 % respectively as the demand for eMBB services further reduced. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 54 0 100 0 100 13:00 Shared resources 0 100 MaxRatio 0 100 0 100 0 100 0 100 0 100 MinRatio DedicatedRatio 0 100 15:00 17:00 19:00 20:00 21:00 22:00 24:00 S-NSSAI#1 S-NSSAI#2 10 20 25 75 50 75 80 60 30 45 15 60 30 10 45 10 25 60 20 60 75 25 65 80 10 25 60 Time MaxRatio MinRatio DedicatedRatio Prioritized resources Dedicated resources Figure 4.6.5-2: Example of network slice resource allocations for O-DU
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4.7 Use case 7: Massive MIMO optimization use cases
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4.7.0 Introduction
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Massive MIMO optimization is one of the top priority use cases in O-RAN. Several massive MIMO sub-features have been proposed and studied during the massive MIMO pre-normative study, which is documented in the O-RAN.WG1.MMIMO-USE-CASES-TR-v00.13 [i.3], including the potential data requirements for each of the sub-use cases. The following clauses provide the background, objectives, solutions, deployment options, and identified WG2 requirements for massive MIMO sub-features
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4.7.1 Massive MIMO Grid-of-Beams Beamforming (GoB BF) optimization
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4.7.1.1 Background and goal of the use case
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Massive MIMO (mMIMO) is among the key methods to increase performance and QoS in 5G networks. Capacity enhancement is obtained by means of beamforming of the transmitted signals, and by spatially multiplexing data streams. Beamforming can increase the received signal power and simultaneously decrease the interference generated for other users, hence resulting in higher SINR and higher user throughputs. Grid-of-Beams (GoB) with the corresponding beam sweeping has been introduced to allow beamforming of the control channels used during initial access as well as for data transmission and reception, mainly for high frequency (but can be used also for the sub-6 GHz band) MIMO operation. The physical properties of the antenna array and its possible configurations characterize the span of the beams, namely the horizontal and vertical aperture in which beamforming is supported, and therefore the coverage area and the shape of the cell. mMIMO can be deployed in 5G macrocell clusters as well as in heterogeneous networks, where macrocells and small cells co-exist and complement each other for better aggregated capacity and coverage. In order to obtain optimal beamforming and cell resources (Tx power, PRB) configuration, one will have to look at a multi-cell environment instead of a single cell. Moreover, different vendors can have different implementations in terms of the number of beams, the horizontal/vertical beam widths, azimuth and elevation range, to achieve the desired coverage. In a multi-node/multi-vendor scenario, centralized monitoring and control is required to offer optimal coverage, capacity and mobility performance as well as control over electromagnetic emissions in order to comply with regulatory requirements. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 55 The problem associated with traditional mMIMO BF is that its performance is highly dependent on the choice of the Beam Forming (BF) pattern. Manual configuration is usually based on the empirical knowledge and manual test results of the domain expert(s) and is performed in a semi-static way. That is, (near-)real time contextual, per-site information (such as cell geometry change, user/traffic distribution, mobility patterns, seasonalities, etc.) is taken into account in a suboptimal and non-real-time way. This can cause one or more of the following problems: 1) High inter-cell interference. 2) Unbalanced traffic between neighbouring cells. 3) Low performance at the cell edges or throughout the cell. 4) Poor handover performance. This solution proposes a framework that allows the operator to flexibly configure the mMIMO BF parameters in a cell or in a cluster of cells by means of policies and configuration assisted by Machine Learning (ML) techniques. The configuration optimization relies on contextual information and patterns such as the user distribution, traffic demand distribution, cell geometries, and mobility.
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4.7.1.2 Entities/resources involved in the use case
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1) SMO & Non-RT RIC Framework (FW): a) Collect the necessary configurations, performance indicators, and measurement reports from the E2 nodes (O-DU), triggered by Non-RT RIC FW if required. b) Transfer collected data towards rApp. c) Provide optimized mMIMO GoB parameters via O1 (to O-DU) or open FH M-plane (to O-RU) interface. d) Optional: Retrieve necessary enrichment information (UE location related information, e.g. GPS coordinates) for the purpose of i) training relevant rApps and ii) execution of relevant rApps. NOTE 1: Exposure of enrichment information to rApps is not defined in the present document. e) Monitor the performance of the respective cells; when the optimization objective fails, initiate fallback procedure and/or trigger the rApp model retraining and re-optimization. f) Execute the inference/control loop periodically or event-triggered. g) Optional: The ML model training can be done by the Non-RT RIC FW. 2) rApps: a) Retrieve the necessary configurations, performance indicators, and measurement reports from the E2 nodes and necessary enrichment information via the SMO, for the purpose of training and execution of relevant AI/ML models. b) Infer an optimized GoB BF configuration. 3) E2 nodes & O-RU: a) Collect and provide necessary measurements and KPIs to the SMO (see Required data clause). b) Apply mMIMO GoB configuration received from the SMO. NOTE 2: Both aggregated and disaggregated gNB architecture are supported.
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4.7.1.3 Solutions
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The context of the creation and deployment of mMIMO GoB BF optimization applications is captured in table 4.7.1.3-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 56 Table 4.7.1.3-1: Creation and deployment of mMIMO GoB BF optimization applications Use Case Stage Evolution / Specification <<Uses>> Related use Goal Optimized beamforming configuration with the Grid-of-Beams method. Actors and Roles SMO, Non-RT RIC, E2 nodes, O-RU. Assumptions All relevant functions and components are instantiated. O1 and OFH-MP interface connectivity is established. Pre-conditions Near-RT RIC and Non-RT RIC are instantiated. O1 interface is established between SMO and Near-RT RIC and E2 nodes, OFH-MP is established between O-DU(s) and O-RU(s). Begins when GoB BF optimization rApp with initial ML model is deployed. Step 1 (M) SMO/Non-RT RIC FW collects the necessary configurations, performance indicators, and measurement reports from E2 nodes (O-DU). Step 2 (O) SMO/Non-RT RIC FW collects input data from external apps. Step 3-6 (M) Collected data is transferred to rApp from the SMO/Non-RT RIC FW and rApp trains the necessary ML model(s). Step 7-10 (M) A new optimization trigger is applied or re-optimization of the GoB BF is necessary due to low performance. ML model assisted rApp infers optimized GoB BF configuration and transfers it to the SMO/Non-RT RIC. Step 11-13 (M) SMO/Non-RT RIC FW applies the optimized GoB BF configuration via O1 or via O1 and OFH-MP. Step 14-20 (O) SMO/Non-RT RIC FW continuously monitors GoB BF performance in respective cells. Optionally, it initiates fallback in case performance is unsatisfactory and requests ML model retraining/update. Then, rApp retrains/updates the respective ML model(s). Ends when On operator request of rApp is disabled. Exceptions None identified. Post Conditions GoB BF configuration is active. Traceability REQ-Non-RT-RIC-FUN1, REQ-Non-RT-RIC-FUN5, REQ-Non-RT-RIC- FUN6, REQ-Non-RT-RIC-FUN8, REQ-Non-RT-RIC-FUN9 The flow diagram of GoB BF optimization is given in figure 4.7.1.3-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 57 Figure 4.7.1.3-1: Flow diagram of GoB BF optimization ETSI ETSI TS 104 226 V10.1.0 (2025-08) 58
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