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7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7 Use case 7: Massive MIMO optimization use cases | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.0 Introduction | 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 c... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.1 Massive MIMO Grid-of-Beams Beamforming (GoB BF) optimization | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.1.1 Background and goal of the use case | 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 g... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.1.2 Entities/resources involved in the use case | 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) ... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.1.3 Solutions | 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 b... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.1.4 Required data | The specification of the data communicated over O1 is outside the scope of WG2. There are no data that are relevant for the A1 interface. |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.2 Massive MIMO Non-GoB Beamforming (Non-GoB BF) optimization | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.2.0 Introduction | This use case provides the background and motivation for the O-RAN architecture to support Non-Grid of Beams beamforming optimization. Non-RT RIC could be used to train AI/ML models for Non-GoB BF selection xApps, which intelligently recommend best Non-GoB BF modes to a O-gNB or O-DU. Note that non-AI/ML based solution... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.2.1 Background and goal of the use case | Non-GoB BF approaches are an important class of beamforming algorithms for 5G massive MIMO deployments, especially for implementations in sub-6 GHz frequency bands. For example, beam weights can be computed at the O-gNB or O-DU based on channel measurements of Sounding Reference Signals (SRS) without predefined beam se... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.2.2 Entities/resources involved in the use case | 1) SMO/Non-RT RIC: a) Retrieve the number of supported Non-GoB BF modes in O-DU via the O1 interface. b) Retrieve performance measurement data and UE context information (e.g. SRS periodicity) from O-DU via the O1 interface, for each Non-GoB BF mode. c) Collect enrichment information from external sources such as appli... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.2.3 Solutions | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.2.3.1 AI/ML-assisted Non-GoB BF mode selection | Note that data collection over E2 interface and E2 control/policy procedures shown in table 4.7.2.3.1-2 and in figure 4.7.2.3.1-2 are under the scope of WG3. Note that external interface between the Non-RT RIC and the external sources (e.g. application servers) is not specified by O-RAN. The context of the AI/ML-assist... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.2.4 Required data | The specification of the data communicated over O1 is outside the scope of WG2. The following enrichment information from external sources (e.g. application server) are used in model training and inference: • UE location • UE mobility • Time granularity of the enrichment information reports (e.g. integer multiple of a ... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.2.5 A1 enrichment information example | In training phase, the retrieved enrichment information (e.g. UE mobility and location information) needs to be associated with collected per-UE L1/L2 measurement reporting (e.g. L1-RSRP and/or L1-SINR, etc.) and UE context information (e.g. UE-specific SRS periodicity) by the Non-RT RIC. In the inference phase, such d... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.3.0 Introduction | This use case will provide the objective, solutions, and data requirements related to MIMO optimization based on three key sub-features involving downlink transmit power, MIMO pairing enhancement (user separability), and user MIMO mode selection (MU-MIMO or SU-MIMO) that are described in detail in the O-RAN.WG1.MMIMO-U... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.3.1 Background and goal of the use case | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.3.1.1 MIMO downlink transmit power optimization | For general downlink precoding, the downlink transmit power is usually evenly distributed across the UEs. However, depending on the UE separability and path loss deltas, this can result in good cell capacity at the expense of individual UE quality. This can be due to several issues such as cell edge UEs having general ... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.3.1.2 MU-MIMO pairing enhancement (user separability) | Existing channel orthogonality between multiple users is critical to create user separability and allow for the opportunity to share radio frequency resources simultaneously. Failing this, residual interference will be too high to maintain adequate post pairing radio link signal quality levels required to sustain MU-MI... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.3.1.3 MIMO mode selection optimization (MU-MIMO vs SU-MIMO selection) | A successful MU-MIMO operation involves the realization of as many orthogonal radio frequency channel links between multiple spatially separated users as possibly as supported by the implementation software at the digital domain. Key to such realization is the successful beamforming weight determination that enables no... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.3.2 Entities/resources involved in the use case | 1) SMO/Non-RT RIC: a) Retrieve relevant performance measurement data and RAN configurations from O-DU via the O1 interface. b) Perform model training and model deployment based on identified measurement data. c) Perform model performance monitoring and model re-training as required. d) Provide RAN configuration recomme... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.3.3 Solutions | 4.7.3.3.1 MIMO optimization via DL SINR threshold, MU-MIMO pairing, and MIMO mode selection The context of the MIMO optimization via DL Tx power, pairing enhancement, and mode selection is captured in table 4.7.3.3.1-1. Table 4.7.3.3.1-1: MIMO optimization via DL Tx power, pairing enhancement, and mode selection Use Ca... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.3.4 Required data | The specification of the data communicated over O1 is outside the scope of WG2. There are no data that are relevant for the A1 interface. |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.4 AI/ML-based initial access (SS Burst Set) configuration optimization | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.4.1 Background and goal of the use case | 3GPP NR based wireless cellular networks promises to provide leaner system design compared to its predecessors in a bid to improve spectral efficiency, power consumption performance and reduce interferences. Ultra-lean design aims to minimize "always on" reference signal transmissions in the downlink. Synchronization S... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.4.2 Entities/resources involved in the use case | 1) SMO & Non-RT RIC framework: a) Collect the necessary Configuration (CM) parameters, Performance Measurements (PM), Key Performance Indicators (KPI), and measurement report traces from the E2 nodes (O-CU-CP, O-CU-UP, O-DU, O-eNB) and O-RU. b) Allow the rApp to receive the CMs, PMs, KPIs measurement data (collected vi... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.4.3 Solutions | The context of the creation and deployment of mMIMO SSB set optimization applications is captured in table 4.7.4.3-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 69 Table 4.7.4.3-1: Creation and deployment of mMIMO SSB set optimization applications Use Case Stage Evolution / Specification <<Uses>> Related use Goal SSB set o... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.4.4 Required data | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.4.4.1 Input data | 1) Supported SSB configurations per cell (as specified in 3GPP TS 38.331 [20], clause 6.3.2 and in 3GPP TS 28.541 [4], clause 4.3.5). 2) Key Performance Indicator (KPIs) such as integrity and cell/beam mobility KPIs, etc., for service level assurance (as specified in 3GPP TS 28.552 [5] and in 3GPP TS 28.554 [17]). 3) C... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.7.4.4.2 Output data | 1) Inferred SSB set (number of SS blocks, SS beam directions and SS burst periodicity) configuration per cell (as specified in 3GPP TS 28.541 [4], clauses 4.3.39 and 4.3.40). ETSI ETSI TS 104 226 V10.1.0 (2025-08) 71 |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8 Use case 8: Network energy saving use cases | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.0 Introduction | This clause contains the set of energy saving use cases. |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.1 Carrier and cell switch off/on | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.1.1 Background and goal of the use case | Mobile networks often utilize multiple frequency layers (carriers) to cover the same service area. At low load, i.e. when the expected traffic volume is lower than a fixed threshold, ES can be achieved by switching off one or more carriers or entire cells without impairing the user experience. UEs previously served by ... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.1.2 Entities/resources involved in the use case | 1) SMO/Non-RT RIC framework function: a) Collect the configurations, performance indicators and measurement reports (e.g. cell load related information and traffic information, EE/EC measurement reports) from E2 node(s) and trace records (e.g. per-UE measurement metrics and location information) through O1 Interface, f... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.1.3 Solution | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.1.3.1 O1 interface based carrier and cell switch off/on optimization for energy saving | In this solution, decision making, potentially including AI/ML model training and inference, is done at the Non-RT RIC. The context of the O1 interface based carrier and cell switch off/on optimization for energy saving is captured in table 4.8.1.3.1-1. Table 4.8.1.3.1-1: O1 interface based carrier and cell switch off/... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.1.3.2 A1 policy based carrier and cell switch off/on optimization for energy saving | In this solution, decision making, potentially using AI/ML model inference, is done at Near-RT RIC. While AI/ML model training might be hosted in Non-RT or Near-RT RIC, the description below is based on AI/ML model training in the Non-RT RIC. The context of the A1 policy based carrier and cell switch off/on optimizatio... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.1.4 Required data | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.1.4.0 Introduction | This clause contains the input and output data of model training and inference for energy saving cell and carrier shutdown. |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.1.4.1 Input data | The measurement input data are used in model training and inference. They can include the following measurements to monitor energy consumption and energy efficiency of E2 node(s) and O-RU(s): a) DL PDCP SDU data volume per interface (data volume in DL delivered from O-CU-UP to O-DU, per PLMN, per QoS level, per slice, ... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.1.4.2 Output data | rApps to deliver energy saving & energy efficiency policies for cell/carrier switch off/on optimization through R1 interface. |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.2 RF channel reconfiguration | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.2.1 Background and goal of the use case | In mobile networks m-MIMO antennas are used for beamforming techniques to enhance cell capacity and throughput. To achieve beamforming, O-RU(s) need to concentrate the power amplifiers at the radome by combining radiating elements. At low load, i.e. when the expected traffic volume or number of connected users are lowe... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.2.2 Entities/resources involved in the use case | 1) SMO/Non-RT RIC framework function: a) Collect the configurations, performance indicators and measurement reports (e.g. cell load related information and traffic information, EE/EC measurement reports) from E2 node(s), for the purpose of decision making, optionally using training and inference of AI/ML models that as... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.2.3 Solution | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.2.3.1 O1 policy based RF channel reconfiguration optimization for energy saving | In this solution, decision making, potentially including AI/ML model training and inference, is done at the Non-RT RIC. The context of the O1 interface based RF channel reconfiguration optimization for energy saving is captured in table 4.8.2.3.1-1. Table 4.8.2.3.1-1: O1 interface based RF channel reconfiguration optim... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.2.3.2 A1 policy based RF channel reconfiguration optimization for energy saving | In this solution, decision making, potentially using AI/ML model inference, is done at Near-RT RIC. While AI/ML model training might be hosted in Non-RT or Near-RT RIC, the description below is based on AI/ML model inferencing in the Near-RT RIC. The context of the A1 policy based optimization for energy saving is capt... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.2.4 Required data | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.2.4.0 Introduction | This clause contains the input and output data of model training and inference for energy saving using RF channel reconfiguration. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 87 |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.2.4.1 Input data | The measurement input data are used in model training and inference. They can include the following measurements to monitor energy consumption and energy efficiency of E2 node(s) and O-RU(s): a) DL PDCP SDU data volume per interface (data volume in DL delivered from O-CU-UP to O-DU, per PLMN, per QoS level, per slice, ... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.2.4.2 Output data | rApps to deliver energy saving & energy efficiency A1 policies for RF channel reconfiguration optimization through R1 interface. |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.3 Advanced sleep mode | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.3.0 Introduction | This use case describes a method to achieve intelligent energy saving by optimizing the sleep mode via Non-RT RIC-based guidance. |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.3.1 Background and goal of the use case | Mobile networks were often designed to provide higher data rates, better coverage, and ubiquitous connectivity. They have to be always available and well-dimensioned in order to ensure the best Quality of Service (QoS) even in peak hours and emergency or mass event scenarios. This may lead to an over-dimensioned and un... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.3.2 Entities/resources involved in the use case | 1) SMO/Non-RT RIC framework function: a) Collect the configurations, performance indicators and measurement reports (e.g. cell load related information and traffic information, EE/EC measurement reports) from E2 node(s) and trace records (e.g. per-UE measurement metrics and location information) through O1 interface, f... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.3.3 Solution | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.3.3.1 A1 policy based ASM optimization for energy saving | In this solution, decision making, potentially using AI/ML model inference, is done at Near-RT RIC. While AI/ML model training might be hosted in Non-RT or Near-RT RIC, the description below is based on AI/ML model inferencing in the Near-RT RIC. The context of the A1 policy based ASM optimization for energy saving is ... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.3.4 Required data | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.3.4.0 Introduction | This clause contains the input and output data of model training and inference for energy saving using ASM. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 92 |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.3.4.1 Input data | The measurement input data are used in model training and inference. They can include the following measurements to monitor energy consumption and energy efficiency of E2 node(s) and O-RU(s): a) DL PDCP SDU data volume per interface (data volume in DL delivered per PLMN, per QoS level, per slice, per interface ((from O... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.8.3.4.2 Output data | rApps to deliver energy saving & energy efficiency policies for ASM optimization through R1 interface. |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.9 Use case 9: O-Cloud resource optimization use cases | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.9.0 Introduction | This clause contains the set of O-Cloud resource optimization use cases. |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.9.1 Use case: O-Cloud node draining use case | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.9.1.0 Introduction | This use case describes the procedure for the SMO/Non-RT RIC to perform draining of specific O-Cloud node [O-Cloud node description based on O-RAN.WG6.O2-GA&P [13] recommendation by rApp through SMO, which can result in relocation of network functions or its components to another O-Cloud node, thereby restoring network... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.9.1.1 Background and goal of the use case | When one or more NF(s) is (are) experiencing some performance degradation, and there is possibility that issue could not be fixed, or root cause could not be identified just by analysing O1 (FCAPS) data. There can be a requirement of co- relating O1 and O2 (FCAPS) data optionally with the help of AI/ML, which can resul... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.9.1.2 Entities/resources involved in the use case | 1) SMO/Non-RT RIC framework: - To collect necessary performance, configuration, and other data for rApp to define and update policies which guides the SMO for O-Cloud resource management through O2 related functions over O2 interface. - Non-RT RIC framework should support rApp for managing data to and from O2 related f... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.9.1.3 Solutions | In this solution, decision making, potentially using AI/ML model inference, is done at rApp. While AI/ML model training might be hosted in Non-RT RIC, the description below is based on AI/ML model training in the Non-RT RIC. The context of Non-RT RIC based O-Cloud node draining is captured in table 4.9.1.3-1. Table 4.9... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.9.1.4 Required data | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.9.1.4.0 Introduction | This clause contains the input and output data required for O-Cloud node drain. |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.9.1.4.1 Input data | O2 related data (O-Cloud FCAPS data): 1) DMS telemetry data to understand state and health of network functions deployed on O-Cloud node. 2) IMS telemetry data to understand the state and health of O-Cloud nodes. 3) IMS/DMS inventory data to understand configuration of nodes and network functions deployments on O-Cloud... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 4.9.1.4.2 Output data | O2 related data: 1) rApp to provide policy based guidance or trigger recommendations to drain O-Cloud node towards O2 related function (NFO/ FOCOM). |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 5 Requirements | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 5.1 Functional requirements | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 5.1.1 Non-RT RIC functional requirements | The Non-RT RIC functional requirements are captured in table 5.1.1-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 98 Table 5.1.1-1: Non-RT RIC functional requirements REQ Description Note REQ-Non-RT-RIC-FUN1 Non-RT RIC shall support data retrieval and analysis; the data can include performance, configuration or other data r... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 5.1.2 A1 interface functional requirements | The A1 interface functional requirements are captured in table 5.1.2-1. Table 5.1.2-1: A1 interface functional requirements REQ Description Note REQ-A1-FUN1 A1 interface shall support communication of policies from Non-RT RIC to Near-RT RIC. REQ-A1-FUN2 A1 interface shall support AI/ML model deployment and update from ... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 5.1.3 R1 interface functional requirements | The R1 interface functional requirements are captured in table 5.1.3-1. ETSI ETSI TS 104 226 V10.1.0 (2025-08) 99 Table 5.1.3-1: R1 interface functional requirements REQ Description Note REQ-R1-FUN1 R1 interface shall support registration of services. Based on REQ- nRTRfW-R1r-10 REQ-R1-FUN2 R1 interface shall support d... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 5.2 Non-functional requirements | |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 5.2.1 Non-RT RIC non-functional requirements | The Non-RT RIC non-functional requirements are captured in table 5.2.1-1. Table 5.2.1-1: Non-RT RIC non-functional requirements REQ Description Note REQ-Non-RT-RIC-NON-FUN1 Non-RT RIC shall not update the same policy or configuration parameter for a given Near-RT RIC or RAN function more often than once per second. REQ... |
7e4409c8abd9ce1b6236b46207489f8c | 104 226 | 5.2.2 A1 interface non-functional requirements | The A1 interface non-functional requirements are captured in table 5.2.2-1. Table 5.2.2-1: A1 interface non-functional requirements REQ Description Note 5.2.3 R1 interface non-functional requirements The R1 interface non-functional requirements are captured in table 5.2.3-1. Table 5.2.3-1: R1 interface non-functional r... |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 1 Scope | This Technical Specification (TS) specifies the technical realization of the handling of calls originated by a GSM mobile subscriber and calls directed to a GSM mobile subscriber, up to the point where the call is established. Normal release of the call after establishment is also specified. The handling of DTMF signal... |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 2 Normative references | The following documents contain provisions which, through reference in this text, constitute provisions of the present document. - References are either specific (identified by date of publication, edition number, version number, etc.) or non-specific. - For a specific reference, subsequent revisions do not apply. - Fo... |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 3 Definitions and abbreviations | |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 3.1 Definitions | For the purposes of the present document, the following definitions apply: A subscriber: The calling mobile subscriber. B subscriber: The mobile subscriber originally called by the A subscriber. C subscriber: The subscriber to whom the B subscriber has requested that calls be forwarded. The C subscriber may be fixed or... |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 3.2 Abbreviations | For the purposes of the present document, the following abbreviations apply: A&O Active & Operative ACM Address Complete Message ANM ANswer Message AoC Advice of Charge BC Bearer Capability BOIC-exHC&BOIZC Barring of Outgoing International Calls except those directed to the HPLMN Country & Barring of Outgoing InterZona... |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 4 Architecture | Subclauses 4.1 and 4.2 show the architecture for handling a basic MO call and a basic MT call. A basic mobile-to- mobile call is treated as the concatenation of an MO call and an MT call. |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 4.1 Architecture for an MO call | A basic mobile originated call involves signalling between the MS and its VMSC via the BSS, between the VMSC and the VLR and between the VMSC and the destination exchange, as indicated in figure 1. MS VMSCA VLRA VPLMNA Radio I/F signalling SIFOC Complete call IAM (ISUP) BSSA 'A' I/F signalling Figure 1: Architecture fo... |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 4.2 Architecture for an MT call | A basic mobile terminated call involves signalling as indicated in figure 2. Communication between VMSCB and the MS is via the BSS, as for the mobile originated case. The IPLMN, containing GMSCB, is in principle distinct from HPLMNB, containing HLRB, but the practice for at least the majority of current GSM networks is... |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 5 Information flows | |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 5.1 Information flow for an MO call | An example information flow for an MO call is shown in figure 3; many variations are possible. Signalling over the radio interface between MSA and BSSA or VMSCA is shown by dotted lines; signalling over the "A" interface between BSSA and VMSCA is shown by dashed lines; signalling over the B interface between VMSCA and ... |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 5.3 Information flow for an MT call | An example information flow for an MT call is shown in figure 5; many variations are possible. ISUP signalling between GMSCB and VMSCB is shown by solid lines; signalling over the B interface between VMSCB and VLRB is shown by chain lines; signalling over the "A" interface between VMSCB and BSSB is shown by dashed line... |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 6.1 Line identification services (GSM 03.81) | |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 6.1.1 Calling Line Identification Presentation (CLIP) | The basic call handling processes ICH_VLR and ICH_MSC interact with the processes CLIP_MAF001 and CLIP_MAF002 (ETS 300 542 [7]) as described in subclauses 7.3.2 and 7.3.1. |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 6.1.2 Calling Line Identification Restriction (CLIR) | The basic call handling processes OCH_MSC and OCH_VLR interact with the processes CLIR_MAF004 and CLIR_MAF003 (ETS 300 542 [7]) as described in subclauses 7.1.1 and 7.1.2. |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 6.1.3 Connected Line Identification Presentation (COLP) | The basic call handling processes OCH_MSC and OCH_VLR interact with the processes COLP_MAF006 and COLP_MAF005 (ETS 300 542 [7]) as described in subclauses 7.1.1 and 7.1.2. The basic call handling processes MT_GMSC and ICH_MSC interact with the process COLP_MAF039 [7] as described in subclauses 7.2.1 and 7.3.1. |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 6.1.4 Connected Line Identification Restriction (COLR) | The basic call handling processes ICH_VLR and ICH_MSC interact with the processes COLR_MAF040 and COLR_MAF041 (ETS 300 542 [7]) as described in subclauses 7.3.2 and 7.3.1. |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 6.2 Call forwarding services (GSM 03.82) | |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 6.2.1 Call Forwarding Unconditional (CFU) | The basic call handling process SRI_HLR interacts with the process MAF007(ETS 300 543 [8]) as described in subclause 7.2.2 |
4adb5594a028990749bbb6b19a2cf30e | 101 043 | 6.2.2 Call Forwarding on mobile subscriber Busy (CFB) | The basic call handling process ICH_VLR interacts with the process MAF008 (ETS 300 543 [8]) as described in subclause 7.3.2 |
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