R18 5G Wireless Group RAN1 Technical Highlights

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.