Company

Sony

6 contributions across 1 work items
6
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 — Proposes supporting CIR reporting for data collection, requires association of data sample parts, and supports model transfer from LMF to UE/gNB.
  • 9.1.3 — Proposes framework allowing UE to carry out predictions for [N] slots simultaneously. Presents options for slot selection. Proposes specifying CSI-RS values with NMSE or channel matrices with NMSE/SGCS. Emphasizes ground truth availability in prediction slot.

Recent contributions

R1-2500642 RAN1_120 NR_AIML_air
Discussion on Specification Support for Beam Management
Sony presents 18 proposals regarding AI/ML-based beam management for NR, focusing on model inference timing, reporting content, and model monitoring mechanisms. The document supports specific options for reference time configuration in…
R1-2500643 RAN1_120 NR_AIML_air
Specification support for AI/ML for positioning accuracy enhancement
Sony submits a contribution for RAN1 Meeting #120 focusing on AI/ML for NR Air Interface positioning accuracy enhancements, presenting 13 proposals across data collection, model input/output, inference consistency, and performance…
R1-2500644 RAN1_120 NR_AIML_air
Specification Support for AI/ML CSI prediction
Sony presents a technical contribution for 3GPP RAN1 regarding specification support for AI/ML-based CSI prediction in the NR Air Interface. The document identifies three key areas requiring standardization: the temporal framework for…
R1-2410216 RAN1_119 NR_AIML_air
Discussion on specification support for beam management
Sony's document presents 18 proposals addressing AI/ML-based beam management for 5G NR, focusing on model inference procedures, time synchronization requirements, and performance monitoring mechanisms for both UE-side and network-side AI…
R1-2410217 RAN1_119 NR_AIML_air
Support for AI/ML for positioning accuracy enhancement
Sony's contribution presents a comprehensive framework for AI/ML-enhanced positioning in NR, covering the entire AI/ML lifecycle from data collection to model deployment and monitoring. The document contains 15 detailed proposals…
R1-2410218 RAN1_119 NR_AIML_air
Further views on consistency issues in CSI prediction
Sony's contribution addresses consistency issues between AI/ML model training and inference for CSI prediction in NR systems, presenting 2 specific proposals for RAN1 study. The document identifies how differences in UE capabilities,…