Company

TCL

7 contributions across 1 work items
7
Tdocs
1
Work items

Recent position changes

AI-synthesized from contributions · all text is paraphrased
RAN1#120 vs RAN1#119 Feb 17, 2025
NR_AIML_air
New positions this meeting
  • 9.1.2 — Prefers Option A-2 for label-based monitoring, proposes signaling monitoring outcomes only upon deterioration, and introduces AI-specific reference signal configurations.
  • 9.1.3 — Proposes UE-requested data collection for training, NW-indicated collection for inference/monitoring, and reusing legacy feedback mechanism for TypeII-Doppler-r18'.

Recent contributions

R1-2500319 RAN1_120 NR_AIML_air
Discussion on CSI Prediction
TCL presents 13 proposals regarding AI-based CSI prediction using UE-side models, covering data collection, model inference, and performance monitoring. The document argues for UE-initiated data collection for training, NW-indicated…
R1-2500555 RAN1_120 NR_AIML_air
Discussion on AIML beam management
TCL proposes integrating AI/ML into NR beam management to simplify the conventional P1/P2/P3 processes into two phases and unify Beam Failure Detection (BFD) and Recovery (BFR) procedures. The document contains 11 proposals and 6…
R1-2500556 RAN1_120 NR_AIML_air
Discussion on AIML positioning
TCL presents 11 proposals and 2 observations regarding specification support for AI/ML-based positioning in NR, focusing on performance monitoring, training data collection, and consistency between training and inference. The document…
R1-2410202 RAN1_119 NR_AIML_air
Discussion on AIML CSI compression
TCL presents a comprehensive technical contribution on AI/ML CSI compression for NR air interface, addressing resource configuration, priority rules, UE capabilities, collaborative training, and overhead reduction. The document contains 7…
R1-2410203 RAN1_119 NR_AIML_air
Discussions on other aspects of AlML In NR air interface
TCL presents a discussion on AI/ML framework aspects for NR air interface, focusing on model identification and additional conditions management. The document contains 3 observations and 3 proposals addressing ID hierarchical…
R1-2410204 RAN1_119 NR_AIML_air
Discussion on AIML beam management
TCL proposes comprehensive enhancements to 3GPP NR beam management by integrating AI/ML techniques to simplify conventional P1/P2/P3 beam pairing processes and improve beam failure detection/recovery procedures. The document contains 10…
R1-2410215 RAN1_119 NR_AIML_air
Discussion on specification support for positioning accuracy enhancement
TCL presents their position on AI/ML based positioning for NR air interface, covering performance monitoring, training data collection, and consistency between training and inference. The document contains 11 proposals and 2 observations…