Company
Lenovo
8 contributions across 1 work items
8
Tdocs
1
Work items
Recent position changes
AI-synthesized from contributions · all text is paraphrased
New positions this meeting
- 9.1.1 — Proposes UE-initiated beam management for data collection, combines associated ID with performance monitoring, proposes overhead reduction techniques, and introduces AI Process Units (APUs).
- 9.1.2 — Proposes extending sample-based measurement definitions to UE-based Cases 1 and 2b, supports CIR and legacy measurements as inputs, and proposes a new UE-based positioning method for Direct AI/ML Case 1.
- 9.1.3 — Proposes reusing AI/ML framework for Beam Management. Requires urgent decision on NW-side additional conditions. Argues against model training at NW with transfer to UE. Prefers deprioritizing model identification techniques, focusing on associated ID and monitoring-based techniques.
Recent contributions
AI/ML specification support for beam management
Lenovo submits 27 proposals for AI/ML-enabled beam management in NR Rel-19, addressing data collection, model inference, and performance monitoring for both UE-side and NW-side models. The document focuses on specification support for…
Specification impacts for AI/ML positioning
Lenovo submits 28 proposals and 1 observation to advance the specification of AI/ML-based positioning in NR, focusing on sample-based measurement definitions, model input/output types, training data construction, and model management. The…
Specification support for CSI prediction
Lenovo proposes reusing the AI/ML framework for Beam Management (BM) for CSI prediction, emphasizing an urgent decision on network-side additional conditions and defining performance monitoring types. The document contains 18 proposals and…
AI/ML specification support for beam management
This Lenovo contribution presents 26 proposals for AI/ML specification support in NR beam management, covering data collection, model inference for both UE-side and NW-side implementations, performance monitoring, and UE capability…
Specification impacts for AI/ML positioning
Lenovo's comprehensive technical document on AI/ML positioning for 3GPP RAN1, presenting 30 proposals and 4 observations covering specification impacts for enhanced positioning accuracy. The document addresses measurement definitions,…
On AI/ML for CSI prediction
Lenovo's document analyzes training/inference consistency challenges for UE-sided AI/ML-based CSI prediction in 5G NR, presenting 7 key proposals and 8 observations. The contribution evaluates four approaches to maintain consistency and…
On AI/ML for CSI compression
Lenovo's technical contribution on AI/ML for CSI compression addresses data collection, model monitoring, inter-vendor collaboration, and quantization schemes. The document contains 19 specific proposals across 6 major technical areas,…
Discussion on other aspects of AI/ML model and data
Lenovo's document discusses model identification procedures for two-sided AI/ML models in CSI compression, focusing on inter-vendor training collaboration options. The document contains 9 key proposals addressing model structure sharing,…