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I. The RRC_INACTIVE state is a fundamental architectural innovation in 5G (NR), designed to address the critical latency and signaling overhead issues that plagued LTE networks. In 4G (LTE), frequent transitions between the RRC_IDLE and RRC_CONNECTED states of the terminal (UE) caused a huge network signaling load and introduced latency penalties during service recovery, which is particularly problematic for modern smartphone usage patterns characterized by frequent small data transmissions. The RRC_INACTIVE state bridges the gap between fully connected and fully disconnected states, enabling fast service recovery while maintaining power efficiency and reducing core network signaling. II. The need for RRC_INACTIVE stems from the limitations of 4G (LTE) and the requirements of 5G: In 4G (LTE) networks, prolonged user inactivity triggers a transition to the RRC_IDLE state to save power. However, restoring to the RRC_CONNECTED state requires re-establishing the RRC connection, which involves a large amount of RRC signaling interaction and introduces significant latency. In modern mobile applications, terminals frequently generate bursts of small data packets (such as social media updates, instant messages, and IoT sensor data), leading to repeated "IDLE-CONNECTED-IDLE" state transitions, burdening both the radio interface and the core network. III. The advantages of RRC_INACTIVE are threefold: Reduced signaling overhead: Both the UE and the gNB store the UE's access stratum (AS) context, so a complete RRC re-establishment process is not required during service recovery. Reduced transition latency: The state transition from INACTIVE to CONNECTED is much faster than from IDLE to CONNECTED because the radio bearer configuration is retained. Maintained core network connectivity: The UE remains in the CM-CONNECTED state relative to the 5G core network (5GC), meaning that the UE's connection on the NG interface between the gNB and the AMF remains active. IV. RRC State Architecture: A 5G (NR) terminal (UE) can be in three different RRC states: RRC_IDLE: The RRC connection does not exist; the UE performs cell selection/reselection and listens for paging. Both the UE and the network's AS context have been released. RRC_INACTIVE: The RRC connection is suspended, and the AS context is retained; the UE monitors paging within the configured RAN Notification Area (RNA), and its behavior is similar to the IDLE state to save power. RRC_CONNECTED: The RRC connection is active and dedicated resources have been allocated; the UE exchanges user plane and control plane data. V. Terminal (UE) Connection Management: In the 5G system, terminal (UE) connection management in the NAS (Non-Access Stratum) interacts with RRC in two states; these are: CM-IDLE: Corresponds to the RRC_IDLE state; there is no NG connection between the gNB and AMF; CM-CONNECTED: Corresponds to the RRC_CONNECTED and RRC_INACTIVE states; the NG signaling connection between the gNB and AMF remains active.

3GPP Release 18 is the first 5G-Advanced version, focusing on AI/ML integration, extreme performance for XR/Industrial IoT, mobile IAB, enhanced positioning, and spectrum efficiency up to 71GHz. RAN1 further promotes AI/ML in RAN optimization and artificial intelligence (PHY/AI) enhancements through physical layer evolution. I. Key Features of RAN1 (Physical Layer and Artificial Intelligence/Machine Learning Innovation) 1.1 MIMO Evolution: Multi-panel uplink (8 layers), MU-MIMO with up to 24 DMRS ports, multi-TRP TCI framework.   Working Principle: Extends Type I/II CSI reporting through a unified TCI framework across multiple TRP panels. The gNB schedules up to 24 DMRS ports for MU-MIMO (12 in Rel-17), enabling each UE to use 8 layers of UL links; DCI indicates the joint TCI state; the UE applies phase/precoding across panels. Progress: Rel-17 multi-TRP lacked unified signaling, resulting in a 20-30% loss in spectral efficiency in dense deployments; layer limitations restricted each UE's UL throughput to 4-6 layers, achieving a 40% increase in uplink (UL) capacity for stadiums/music festivals. 1.2 AI/ML applied to CSI feedback compression, beam management, and positioning.   Working Principle: Neural networks use offline-trained codebooks to compress Type II CSI (32 ports → 8 coefficients). The gNB deploys the model via RRC; the UE reports the compressed feedback. Beam prediction uses L1-RSRP patterns to pre-position beams before handover. Project Progress: CSI overhead consumes 15-20% of DL resources; beam management failure rate is as high as 25% in high-mobility scenarios (e.g., highways). Improved Results: 50% reduction in Channel State Information (CSI) overhead, 30% increase in handover success rate. 1.3 Coverage Enhancement (Uplink full power transmission, low-power wake-up signal).   Working Principle: The gNB sends a signal to the UE to apply full power output on all uplink layers (no layer-level power backoff). An independent low-power wake-up receiver (duty cycle controlled, sensitivity -110dBm) receives the wake-up signal (WUS) before the main reception cycle. The WUS carries 1-bit indication information (monitoring PDCCH or sleep). Project progress: Rel-17 uplink coverage is limited by hierarchical power backoff (3dB loss for 4-layer MIMO); the main receiver consumes 50% of the UE's power during DRX monitoring. Improved effect: Uplink coverage extended by 3dB, 40% power saving for IoT/video streaming applications. 1.4 ITS band Sidelink Carrier Aggregation (CA) and dynamic spectrum sharing (DSS) with LTE CRS.   Working principle: Sidelink supports CA across n47 (5.9GHz ITS) + FR1 bands; supports UE-to-UE coordinated autonomous resource selection of Type 2c. Due to round-trip time (RTT) greater than 500 milliseconds, HARQ is disabled for NTN IoT (only open-loop repetition is supported); Doppler effect pre-compensation is performed in DMRS. Project progress: Rel-17 Sidelink only supports single carrier (50% throughput loss); NTN IoT HARQ timeout results in 30% packet loss. Improved effect: V2X platooning sidelink throughput increased by 2 times, NTN IoT reliability reaches 95%. 1.5 Extended Reality (XR)/Multi-sensor communication (high reliability low latency support).   Working principle: New QoS process, latency budget less than 1 millisecond, supports multi-sensor data packet marking (video + haptic + audio streams). gNB prioritizes through preemption mechanism. UE reports posture/motion data for predictive scheduling. Project progress: Rel-17 XR support only supports unicast; haptic feedback latency exceeds 20 milliseconds (unusable for remote operation). Improved effect: End-to-end latency of AR/VR + haptics in industrial remote control is less than 5 milliseconds. 1.6 NTN function enhancement (smartphone uplink coverage, disabling HARQ for IoT devices).   Working Principle: Rel-18 improves uplink coverage for smartphones in non-terrestrial networks (NTNs) by optimizing physical layer transmission, allowing for higher transmit power and better link budget management to accommodate satellite channels. For IoT devices on NTNs, traditional HARQ feedback is inefficient due to long satellite round-trip time (RTT), so HARQ feedback is disabled and an open-loop retransmission scheme is used instead. Project Progress: Previously, limited uplink coverage for smartphones on NTNs due to insufficient power control and link margin resulted in poor connectivity. HARQ feedback caused throughput degradation and latency issues for IoT devices due to satellite delays. Disabling HARQ eliminates feedback delays and improves reliability for constrained IoT devices. This enables robust global connectivity for IoT and smartphones beyond terrestrial networks. II. RAN1 Project Applications   Dense urban XR (Multi-TRP MIMO technology reduces AR/VR latency to below 1 millisecond); Industrial automation (AI/ML beam prediction reduces handover failure rate by 30%); V2X/High mobility (Sidelink CA improves reliability).   III. RAN1 Project Implementation   gNB PHY (Base Station Physical Layer): Integrates AI models for CSI compression (e.g., neural networks predict Type II CSI based on Type I CSI, reducing overhead by 50%). Deploys multi-TRP TCI via RRC/DCI and uses 2 TAs for uplink timing. Terminal (UE): Supports low-power wake-up receiver (independent of the main RF link) for DRX alignment signaling.

  RAN5 is the User Equipment (UE) Conformance Test Group. Its goal is to establish UE conformance test specifications on the radio interface based on 3GPP core specifications, covering 2G, 3G, 4G, 5G, and future technologies. The test specifications established in Rel-18 include:   I. AI/ML Model and Mobile IAB Conformance (Testing)   Working Principle: TTCN-3 test cases verify MT handover (no-service UE disconnection), NCGI reallocation timing (

  Release 18 defines the RF performance of 5G-Advanced bands/devices within the RAN working group. RAN4's main work includes:   I. Band/Device RF (Performance) Characteristics: FR1 < 5MHz dedicated spectrum FRMCS migrated from GSM-R.  Operating Principle: Coexistence with GSM-R's n100 (1900MHz, 3-5MHz bandwidth) specified ACS/SEM; reduced bandwidth and adjusted power levels for narrowband operation; RRM requirements ensure interference to traditional railways is less than 1%.  Progress: European railways lacked NR spectrum during the migration from GSM-R, and the 5MHz minimum bandwidth limitation prevented coexistence. Results: Actual coexistence tests (m28+n100) showed zero interference. II. RedCap Evolution (positioning via frequency hopping PRS/SRS). Operating Principle: The UE with reduced bandwidth (20MHz) uses frequency hopping PRS within a total bandwidth of 100MHz; gNB coordinates the frequency hopping mode; the UE reports the time of arrival (ToA) for each hop, achieving centimeter-level accuracy. Progress: Due to the narrow bandwidth, Rel-17 RedCap positioning accuracy is limited to within 10 meters. Implementation Results: Positioning accuracy for wearable devices/industrial sensors is less than 1 meter. III. NTN, Sidelink & ITS include NTN (above 10 GHz), Sidelink, and ITS (Intelligent Transportation Systems) radio frequencies;   Operating Principle: Ka-band (17-31 GHz) NTN radio frequencies require ±50 kHz Doppler tolerance and 1000 ms propagation delay. UE power level 3 and beam compatibility are mandatory. The channel model includes atmospheric attenuation and rain attenuation. Progress: Rel-17 NTN is limited to L/S bands; millimeter-wave satellites are subject to propagation obstruction. Implementation Goal: 30 GHz geostationary orbit (GEO) satellite coverage, suitable for backhaul/Internet of Things (IoT). IV. L1/L2 Mobility, XR KPI RRM includes RRM for L1/L2 mobility and XR KPIs. RRM.   Operating Principle: RRM specifications for L1-RSRP measurement (delay

  In the 3GPP Technical Radio Access Network (TSG RAN) specification group, RAN3 is responsible for the overall architecture of UTRAN, E-UTRAN, and G-RAN, as well as the protocol specifications of related network interfaces. Specific details in R18 are as follows:   I. AI/ML and IAB Mobile Architecture for RAN3   1.1 AI/ML for NG-RAN (Model Deployment, F1/Xn-based Inference)   Working Principle: CU/DU exchange AI model parameters (tensor shape, quantization) via F1AP/XnAP. gNB-DU runs inference locally (beam/CSI prediction) and sends the results to CU. The model is updated with incremental parameters (without requiring complete retraining). Progress: Lack of standardized AI integration; vendors use proprietary silos. Implementation Results: Interoperable AI across multi-vendor RANs has been achieved (verified by Ericsson and Nokia). 1.2 Mobile IAB (Node Migration, RACH-less Handover, NCGI Reconfiguration)    Operating Principle: IAB-MT performs L1/L2 handover to the target parent node; the serving user equipment (UE) performs handover via NCGI (NR cell global ID) reallocation. Work Progress: The target gNB allocates UL timing via XnAP before migration. The topology is advertised in the SIB (mobileIAB-Cell). Implementation Results: Static IAB fails during vehicle movement (events cover vehicles, trains); throughput drops by 60% during topology changes. Seamless backhaul migration maintains 5% UE throughput during 60 mph movement.   1.3 SON/MDT Enhancements (RACH Optimization, NPN Logging).   Operating Principle: MDT logs RACH failures and L1/L2 movement events for specific slices. The SON algorithm automatically adjusts the number of RACH operations based on slice load. NPN (Non-Public Network) logging includes enterprise identifiers and coverage maps. Work Progress: Rel-17 SON cannot recognize slice interactions; enterprise NPN lacks diagnostic data. Implementation Results: RAC optimization improved by 40%, NPN deployment verification was automated. 1.4 QoE Framework (AR/MR/Cloud Gaming, RAN-visible QoE based on data center).   Working Principle: gNB collects XR attitude data, rendering latency, and packet loss rate through QoE measurements (MAC CE/RRC). It reports to OAM/NWDAF via XnAP/NGAP. Dynamic QoS adjustment is performed based on video stuttering events and motion sickness indicators. Progress: RAN is unaware of application QoE; operators are unaware of XR performance degradation. Implementation Results: Video stuttering was reduced by 30% through predictive scheduling. 1.5 Network Slicing (S-NSSAI Alternative, Partially Allowing NSSAI).   Working Principle: Partial NSSAI allows the use of a subset during congestion; S-NSSAI is dynamically replaced by NGAP. Timing Synchronization Status (TSS) is reported every 10 seconds during GNSS outages to achieve gNB clock correction. Progress: NSSAI mismatch caused 20% of slice handover failures; GNSS outages caused 15% timing drift in the FR2 band. Implementation Results: NSSAI consistency reached 99%, and timing accuracy during outages was less than 1μs. 1.6 Timing Resilience (NGAP/XnAP TSS Reporting).   Working Principle: The NGAP and XnA protocols were enhanced with the addition of a Timing Synchronization Status (TSS) reporting mechanism between network nodes to detect and compensate for timing drift or GNSS outages. This ensures that gNBs can dynamically adjust their clocks based on TSS messages to maintain synchronization. Progress: Timing alignment is critical for NR, especially in high-frequency bands and NTN. GNSS outages or network failures can cause timing drift, impacting throughput and mobility. The TSS mechanism improves network resilience by enabling rapid correction, reducing link failures and service degradation caused by timing errors.   II. RAN3 Technology Applications Vehicle-mounted Relays (VMR for event coverage). Enterprise-grade NPN Phase 2 (SNPN Reselection/Handover). Automation (AI/ML SON automatically adjusts coverage).   III. RAN3 Practical Applications CU/DU: F1AP extension for AI model parameters (e.g., input/output tensors); Mobile IAB MT migration is achieved through Xn handover. Application Examples: Mobile IAB-DU reselection broadcasts the mobile IAB-Cell indicator; UEs use SIB-assisted priority ranking, thereby reducing topology change latency by 40%.

  RAN2 is responsible for the radio interface architecture and protocols (such as MAC, RLC, PDCP, SDAP), radio resource control protocol specifications, and radio resource management procedures in the 3GPP Radio Access Network (RAN2) technical specifications. RAN2 is also responsible for developing technical specifications for 3G evolution, 5G (NR), and future radio access technologies.   I. Enhanced L1/L2 Mobility and XR Protocols RAN2 focuses on MAC/RLC/PDCP/RRC protocols to achieve mobility, XR, and power efficiency. Key features include:   1.1 L1/L2-centric inter-cell mobility (dynamic cell handover, L1 beam management). Working Principle: In connected mode, the UE measures L1-RSRP via SSB/CSI-RS with no RRC gap. The gNB triggers CHO (Conditional Handover) based on the L1 threshold; the UE performs handover autonomously; L2 handover is performed via MAC CE (without RRC). Progress: Based on RRC, the handover interruption time is 50-100 milliseconds; the handover failure rate on high-speed railways (500 km/h) is as high as 40%. Implementation Results: Interruption time is less than 5 milliseconds, and the handover success rate reaches 95% at a speed of 350 km/h. 1.2 XR Enhancement (Multi-sensor Data, Dual Connectivity Activation).   Working Principle: RRC configures XR QoS streams and performs attitude/motion reports (sending 6 degrees of freedom data every 5 milliseconds). Conditional PSCell activation activates UE measurement SCG L1-RSRP, triggered by MAC CE, without requiring RRC reconfiguration; multi-sensor tagging distinguishes video/haptic/audio streams. Progress: Rel-17 DC activation interruption exceeding 50 milliseconds leads to XR synchronization interruption; multi-sensor QoS cannot be distinguished. Implementation Results: SCG activation latency is less than 10 milliseconds, and the QoS of each sensor stream is independent (haptic priority). 1.3 Multicast Evolution (MBS in RRC_INACTIVE state, dynamic group management). Operating Principle: gNB configures MBS sessions via RRC; inactive UEs join via group ID, requiring no state transition. Dynamic Handover: Unicast to multicast handover is performed based on a UE count threshold. HARQ combines multicast and unicast reception. Work Progress: Rel-17 MBS requires the RRC_CONNECTED state (IoT device power consumption 70%). Result: Software update saves 70% energy, stadium capacity increases by 90%. 1.4 RRC State Optimization (Small data transmitted through inactive state, slice-aware reselection).   Operating Principle: SIB carries slice-specific RACH events/PRACH masks. UEs in idle/inactive states perform slice-aware reselection (prioritizing the highest priority S-NSSAI). UEs in the RRC_CONNECTED state report allowed NSSAI changes during handover. Work Progress: Rel-17's lack of support for slice-aware access resulted in 25% of URLLC UEs accessing eMBB slices. Results: The initial slice access success rate reached 95%. 1.5 Energy Saving (Extended DRX, Reduced Measurement Interval).   How it Works: Extended DRX allows User Equipment (UE) to extend its sleep time by reducing the frequency of paging and control channel listening. Reducing the measurement interval minimizes data transmission interruptions caused by measurement demands by optimizing or combining the measurement interval with other signaling events. Progress: Due to frequent control channel listening and measurement intervals leading to frequent radio state switching, UEs experience high power consumption. By extending the DRX cycle and reducing the measurement interval, battery life is significantly improved across all device categories, especially for IoT devices requiring long-term operation. II. Areas of Improvement: High-speed rail (achieving L1/L2 handover latency

  Two CM (Connection Management) statuses are used in the 5G (UE) system to reflect the NAS signaling connection between the terminal (UE) and the AMF. They are: CM-IDLE CM-CONNECTED   I. 5G Terminal (UE) Connection Status When the terminal accesses 3GPP and non-3GPP systems, its CM status is independent of each other. That is, one CM status can be in CM-IDLE state, while the other CM status can be in CM-CONNECTED state.   II. CM-IDLE State When in CM-IDLE:   2.1 The 5G terminal (UE) has not established a NAS signaling connection with the AMF through N1; at this time, the UE performs cell selection/cell reselection according to TS 38.304[50] and PLMN selection according to TS 23.122[17]. The UE has no AN signaling connection, N2 connection, or N3 connection. If the UE is simultaneously in CM-IDLE and RM-REGISTERED states (unless otherwise specified in Clause 5.3.4.1), the UE shall: Respond to paging by executing the service request procedure (see Clause 4.2.3.2 of TS 23.502 [3]), unless the UE is in MICO mode (see Clause 5.4.1.3); Execute the service request procedure when the UE has uplink signaling or user data to send (see Clause 4.2.3.2 of TS 23.502 [3]). LADN has specific conditions (see Clause 5.6.5).   2.2 When the UE state in the AMF is RM-REGISTERED, the terminal information required to initiate communication with the UE shall be stored. The AMF shall be able to retrieve the stored information required to initiate communication with the UE using 5G-GUTI. ---- In 5GS, paging is not required using the UE's SUPI/SUCI.   2.3 During AN signaling connection establishment, the UE shall provide 5G-S-TMSI as part of the AN parameters in accordance with TS 38.331[28] and TS 36.331[51]. When the UE establishes an AN signaling connection with the AN (entering the RRC_CONNECTED state via 3GPP access, establishing a UE-N3IWF connection via untrusted non-3GPP access, or establishing a UE-TNGF connection via trusted non-3GPP access), the UE shall enter the CM-CONNECTED state. Sending an initial NA message (registration request, service request, or deregistration request) initiates the transition from CM-IDLE to CM-CONNECTED state.   2.4 When the AMF is in the CM-IDLE or RM-REGISTERED state, the AMF should execute a network-triggered service request procedure when it needs to send signaling or mobile terminal data to the UE. This is done by sending a paging request to the UE (see Section 4.2.3.3 of TS 23.502[3]), provided that the UE is not unable to respond due to MICO mode or mobility restrictions. Among them:   When the AN and AMF establish an N2 connection for the UE, the AMF should enter the CM-CONNECTED state. Receiving an initial N2 message (e.g., N2 INITIAL UE MESSAGE) will trigger the AMF to transition from the CM-IDLE state to the CM-CONNECTED state. When the UE is in the CM-IDLE state, the UE and AMF can optimize the UE's power efficiency and signaling efficiency, for example, by activating MICO mode (see Section 5.4.1.3).   III. CM-CONNECTED State The UE in the CM-CONNECTED state establishes a NAS signaling connection with the AMF through N1. NAS signaling connections utilize the RRC connection between the UE and the NG-RAN, and the NGAP UE association between the AN and the AMF, to achieve 3GPP access. The UE can be in the CM-CONNECTED state, but its NGAP UE association is not bound to any TNLA between the AN and the AMF.   For a UE in the CM-CONNECTED state, the AMF can decide to release the NAS signaling connection with the UE after the NAS signaling procedure is completed.   3.1 In the CM-CONNECTED state, the UE should: Enter the CM-IDLE state when the AN signaling connection is released (e.g., entering the RRC_IDLE state via 3GPP access, or when the UE detects the release of the UE-N3IWF connection via an untrusted non-3GPP access, or the release of the UE-TNGF connection via a trusted non-3GPP access).   3.2 When the UE's CM state in the AMF is CM-CONNECTED, the AMF shall:   --When the UE's logical NGAP signaling connection and N3 user plane connection are released after the AN release procedure specified in TS 23.502[3] is completed, the UE shall enter the CM-IDLE state.   --The AMF may maintain the UE's CM state in the CM-CONNECTED state until the UE is deregistered from the core network.   3.3 A UE in the CM-CONNECTED state may be in the RRC_INACTIVE state, see TS 38.300[27]. When the UE is in the RRC_INACTIVE state, the following rules apply: - UE reachability is managed by the RAN and auxiliary information is provided by the core network; - UE paging is managed by the RAN; - The UE listens for paging using its CN (5G S-TMSI) and RAN identifier.

  3GPP Release 18 is the first 5G-Advanced release, focusing on AI/ML integration, ultimate performance in XR/Industrial IoT, mobile IAB, enhanced positioning, and spectrum efficiency up to 71GHz. RAN1 further promotes AI/ML enhancements in RAN optimization and artificial intelligence (PHY/AI) through physical layer evolution.   I. Key Features of RAN1 (Physical Layer and AI/Machine Learning Innovations)   1.1 MIMO Evolution: Multi-panel uplink (Level 8), MU-MIMO with up to 24 DMRS ports, multi-TRP TCI framework.   Operating Principle: Extends Type I/II CSI reporting through a unified TCI framework across multiple TRP panels. The gNB schedules up to 24 DMRS ports for MU-MIMO (12 in Rel-17), enabling each UE to use Level 8 UL links; DCI indicates joint TCI status; UE applies phase/precoding across panels. Progress: The lack of unified signaling in Rel-17 multi-TRP resulted in a 20-30% loss of spectral efficiency in dense deployments; level restrictions limited the UL throughput of each UE to layers 4-6, thereby achieving a 40% increase in uplink (UL) capacity for stadiums/music festivals.   1.2 AI/ML Applications to CSI Feedback Compression, Beam Management, and Positioning.   Working Principle: The neural network uses an offline-trained codebook to compress Type II CSI (32 ports → 8 coefficients). The gNB deploys the model via RRC; the UE reports the compressed feedback. Beam prediction uses the L1-RSRP mode to pre-position beams before handover. Project Progress: CSI overhead consumed 15-20% of DL resources; in high-mobility scenarios (e.g., highways), beam management failure rates reached as high as 25%. Improvement Results: Channel State Information (CSI) overhead reduced by 50%, handover success rate improved by 30%. 1.3 Enhanced Coverage (Uplink full-power transmission, low-power wake-up signal).   Operating Principle: The gNB sends a signal to the UE, enabling it to apply full power output across all uplink layers (without tiered power backoff). An independent low-power wake-up receiver (duty cycle controlled, sensitivity -110dBm) receives the wake-up signal (WUS) before the main receive cycle. The WUS carries 1 bit of indication information (monitoring PDCCH or sleep). Project Progress: Rel-17 uplink coverage is limited by tiered power backoff (4th order MIMO loss of 3dB); the main receiver consumes 50% of the UE's power during DRX monitoring. Improvements: Uplink coverage extended by 3dB; IoT/video streaming applications saved 40% of power. 1.4 ITS Band Sidelink Carrier Aggregation (CA) and Dynamic Spectrum Sharing (DSS) with LTE CRS.   Operating Principle: Sidelink supports CA across the n47 (5.9GHz ITS) + FR1 bands; supports autonomous resource selection for Type 2c coordination among UEs. Due to a round-trip time (RTT) greater than 500 milliseconds, NTN IoT disables HARQ (only supports open-loop repetition); pre-compensation is implemented for the Doppler effect in DMRS. Project Progress: Rel-17 Sidelink only supports single-carrier (50% throughput loss); NTN IoT HARQ timeouts result in 30% packet loss. Improvements: V2X formation sidelink throughput is increased by 2x, and NTN IoT reliability reaches 95%. 1.5 Extended Reality (XR)/Multi-sensor Communication (High Reliability, Low Latency Support).   Operating Principle: New QoS procedure, latency budget less than 1 millisecond, supports multi-sensor packet tagging (video + haptic + audio stream). gNB prioritizes data through a preemption mechanism. UE reports attitude/motion data for predictive scheduling. Project Progress: Rel-17 XR support only supports unicast; haptic feedback latency exceeds 20 milliseconds (unusable for remote operation). Improvements: End-to-end latency of AR/VR + haptic in industrial remote control is less than 5 milliseconds.   1.6 NTN Functionality Enhancement (Smartphone Uplink Coverage, Disabling HARQ for IoT Devices).   How it Works: Rel-18 improves the uplink coverage of smartphones in non-terrestrial networks (NTNs) by optimizing physical layer transmission, allowing for higher transmit power and better link budget management to accommodate satellite channels. For IoT devices on NTNs, traditional HARQ feedback is inefficient due to long satellite round-trip times (RTTs), therefore HARQ feedback is disabled, and an open-loop repetition scheme is adopted instead. Project Progress: Previously, due to insufficient power control and link margin, the uplink coverage of smartphones on NTNs was limited, resulting in poor connectivity. HARQ feedback caused throughput reduction and latency issues for IoT devices due to satellite latency. Disabling HARQ eliminates feedback latency and improves the reliability of constrained IoT devices. This enables robust global connectivity for IoT and smartphones beyond terrestrial networks. II. RAN1 Project Applications Dense Urban XR (Multi-TRP MIMO technology reduces AR/VR latency to below 1 millisecond); Industrial Automation (AI/ML beam prediction reduces handover failure rate by 30%); V2X/High Mobility (Sidelink CA improves reliability).   III. RAN1 Project Implementation gNB PHY (Base Station Physical Layer): Integrates an AI model for CSI compression (e.g., neural networks predict Type II CSI based on Type I CSI, reducing overhead by 50%). Deploys Multi-TRP TCI via RRC/DCI and uses 2 TAs for uplink timing. Terminal Equipment (UE): Supports low-power wake-up receivers (independent of the main RF link) for DRX alignment signaling.

  RAN3 Release 17 focuses on major evolutions in 5G (NR), bringing enhancements to key architectures such as native multi-access edge computing (MEC) support, the introduction of reduced-capacity RedCap for IoT, enhanced sidechains, positioning and MIMO, and increased support for new frequency bands (up to 71 GHz) and non-terrestrial NTN. All of these improvements are built upon core network function evolution to enhance spectrum efficiency and device power saving, enabling broader 5G applications.   I. Key Features of RAN3 in Release-17 IAB Function Enhancements—Improved resource reuse, topology robustness, and routing options between IAB parent and child links. NTN (Non-Terrestrial Network) Architecture—System architecture supports integration of satellite/HAP with terrestrial 5G (NR). NPN (Non-Public Network) Enhancements and Edge Computing Integration Support. II. Key Technical Details and System Integration of RAN3   2.1 Enhanced IAB (Integrated Access and Backhaul) Technology Resource Reuse: Rel-17 defines additional mechanisms that enable IAB nodes to allocate resources more flexibly between access (to UE) and backhaul (to child IAB nodes) based on existing scheduling. Specifically: Updating F1/Xn internal signaling between the parent node and the IAB-DU/MT. Achieving robust path management and rerouting—the IAB control plane (IAB-CU) must be able to reallocate provider relationships in the event of link failure. Topology and Routing: Support for semi-static routing table updates and enhanced bearer mapping; vendors need to test congestion/priority rules for backhaul and access traffic. 2.2 NTN Architecture   GW and NG-RAN Integration: Rel-17 defines NTN Stage 2/Stage 3 architectural changes to support satellite link features end-to-end. Implementers must coordinate with the CN (SA/CT) to support PDU sessions and mobility differences (such as longer handover times due to GEO/LEO satellite movement).   Timing and Synchronization: NTN nodes typically require GNSS/time distribution (or alternative time synchronization) and specific handling of timing advance and HARQ timers within the RAN architecture is necessary.

  RAN2's 5G work focuses on consolidating and enhancing the concepts and functions introduced in R16, while adding new system features; improving vertical industry applications including positioning and dedicated networks; advancing short-range (direct) communication between terminal devices in the field of autonomous driving (V2X) for Internet of Things (IoT) support; improving support for multiple media (codecs, streaming media, broadcast) related to the entertainment industry; and improving support for mission-critical communications. Furthermore, it improves several network functions (such as network slicing, flow control, and edge computing). The specific key points regarding the radio interface architecture and protocols (such as MAC, RLC, PDCP, SDAP), radio resource control protocol specifications, and radio resource management processes under the responsibility of 3GPP RAN2 are as follows:   I. Key Features of RAN2 Rel-17: Sidelink Enhancements (Relay, Multicast, V2X Functionality Extensions). RedCap Protocol Support (Lightweight RRC Status, Energy Saving, Feature Set Reduction). QoE/slice control enhancements and mobility handling (slice improvements and ATSSS interaction). Location enhancement procedures (new measurement methods and reference signal usage). II. Rel-17 Implementation Impact and Details   2.1 Sidelink Enhancements (Relay, Multicast, V2X Functionality Extensions) RRC message and MAC/PHY multiplexing changes; new Sidelink relay (L2/L3) multicast and group management procedures. In application: Extended sidelink control channel processing and HARQ management for relay nodes, RC upgrade to support Sidelink configuration lists, group identifiers, and security context distribution. Resource allocation enhancements support scheduling and autonomous resource selection and add an RRC TLV field for authorization timing and reservation windows. 2.2 RedCap and RRC Reduced RRC complexity: RedCap devices may support fewer RRC states and optional functions (e.g., limited measurements). RAN2 specifies capability signaling and fewer RRC IEs; implementers must ensure that the gNodeB's RRC can handle capability-limited UEs without affecting normal UE processing. Energy-saving timers and RRC inactive: Tight integration with MAC and DRX to optimize power consumption; the scheduler supports longer DRX cycles and fewer grant allocations. 2.3 Location and Measurement Rel-17 introduces new measurement types and reporting formats to improve the application of PRS/CSI-RS in location. Implementation requires changes to UE measurement reports (RRC measurement objects and reports) and the LPP/NRPPa interface of the location server. ​