Company
InterDigital
10 contributions across 1 work items
10
Tdocs
1
Work items
Recent position changes
AI-synthesized from contributions · all text is paraphrased
New positions this meeting
- 9.1.1 — Proposes clarifying data collection signaling, separate CSI-ResourceConfig Ids for Set A/B, shared CPU counter, and overhead reduction via X dB gap reporting.
- 9.1.3 — Argues Associated ID is unnecessary due to high complexity and negligible degradation. Proposes dropping Associated ID requirement, relying on model performance monitoring. Opposes Type 2, supports Type 3. Proposes out-of-distribution metrics alongside intermediate KPIs.
New positions this meeting
- 9.1.1 — Strongly advocates for Option 2 applicability approach for UE-side models to avoid excessive configuration overhead, supporting single CSI-ResourceConfigId configuration and UE-assisted performance monitoring over network-only approaches.
Recent contributions
Reply LS to SA2 on AIML data collection
This document is a Reply Liaison Statement from RAN2 to SA2 regarding AI/ML data collection for NR Air Interface, specifically addressing UE-side model training. It contains six distinct answers to SA2's questions concerning NG-RAN…
Reply LS on AIML data collection
InterDigital reports that SA2 did not reach consensus on the feasibility of standardized UE-side data collection solutions to meet RAN requirements specified in LS RP-242389. The document states that a full evaluation requires further…
Discussion on AI/ML for beam management
InterDigital presents 27 proposals and 14 observations regarding AI/ML for beam management in NR, focusing on data collection configuration, beam prediction reporting overhead reduction, and performance monitoring. The document argues for…
On AI/ML-based CSI prediction
InterDigital presents evaluation results on AI/ML-based CSI prediction, demonstrating that UE-sided models generalize well across antenna down-tilt variations and that localized models offer only minor gains over generalized ones. The…
Discussion on AI/ML for beam management
InterDigital presents 29 proposals and 24 observations regarding AI/ML for beam management in NR, focusing on configuration frameworks, reporting overhead reduction, and lifecycle management. The document argues for Option 2 for UE-side…
Discussion on support for AIML positioning
InterDigital's comprehensive technical document presents 38 proposals and 24 observations for AIML positioning in NR, focusing on Case 1 (UE-based positioning with UE-side model), Case 3a (gNB-side model), and Case 3b (LMF-side model). The…
On AI/ML-based CSI prediction
InterDigital presents evaluation results on AI/ML-based CSI prediction for NR air interface, demonstrating that UE-sided models can generalize well across different network conditions without requiring complex associated ID mechanisms. The…
On AI/ML-based CSI compression
InterDigital presents comprehensive analysis of AI/ML-based CSI compression for NR air interface, covering beam domain processing, temporal-spatial-frequency compression, model monitoring, and inter-vendor collaboration. The document…
On other aspects of AI/ML model and data
InterDigital's contribution addresses AI/ML model identification for two-sided models, data collection for training, and model transfer/delivery aspects for NR air interface. The document contains 14 proposals and 9 observations across…
LS on AIML data collection
This liaison statement from RAN to SA groups presents 4 options for AI/ML data collection for UE-side model training, seeking SA input by RAN#106 to resolve consensus issues on MNO controllability and UP tunnel feasibility. The document…