Company

OPPO

14 contributions across 1 work items
14
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 — Opposes phase information reporting, proposes using associated ID for consistency, and argues against dedicated enhancements for performance monitoring without ground-truth labels.
  • 9.1.3 — Argues no consistency issue for UE-sided CSI prediction, rendering associated ID unnecessary. Prioritizes UE-side data collection. Supports reusing Rel-18 MIMO frameworks. Opposes Type 2, proposes average NMSE for Type 3 with configurable averaging.

Recent contributions

R1-2500465 RAN1_120 NR_AIML_air
On specification for AI/ML-based beam management
OPPO presents a comprehensive set of proposals for AI/ML-based beam management in NR Rel-19, covering both NW-side and UE-side models for BM-Case 1 and BM-Case 2. The document contains approximately 35 distinct proposals and observations,…
R1-2500466 RAN1_120 NR_AIML_air
On specification for AI/ML-based positioning accuracy enhancements
OPPO submits 33 proposals and 3 observations regarding specification impacts for AI/ML-based positioning accuracy enhancements in Rel-19, covering measurement enhancements, training/inference consistency, data collection, model inference,…
R1-2500467 RAN1_120 NR_AIML_air
On specification for AI/ML-based CSI prediction
OPPO presents 13 proposals and 2 observations regarding AI/ML-based CSI prediction, arguing that UE-sided models face no consistency issues and prioritizing UE-side data collection over NW-side model transfer. The document proposes reusing…
R1-2410101 RAN1_119 NR_AIML_air
On specification for AI/ML-based beam management
OPPO's technical document on AI/ML-based beam management for 3GPP RAN1 contains comprehensive responses to RAN2 liaison questions and presents 50+ technical proposals covering NW-side and UE-side model inference, training, monitoring, and…
R1-2410102 RAN1_119 NR_AIML_air
On specification for AI/ML-based positioning accuracy enhancements
OPPO's technical document presents a comprehensive analysis of AI/ML-based positioning accuracy enhancements for NR Release 19, covering five positioning cases (Case 1, 2a, 2b, 3a, 3b) with 26 detailed proposals and 3 observations…
R1-2410103 RAN1_119 NR_AIML_air
On specification for AI/ML-based CSI prediction
OPPO proposes solutions for ensuring consistency between training and inference phases in AI/ML-based CSI prediction for NR air interface, addressing both intra-cell and inter-cell scenarios. The document contains 5 proposals and 3…
R1-2410104 RAN1_119 NR_AIML_air
Additional study on AI/ML-based CSI compression
OPPO presents analysis on inter-vendor collaboration approaches for AI/ML-based CSI compression, evaluating multiple directions and options for standardization. The document contains 17 proposals and 5 observations covering reference model…
R1-2410105 RAN1_119 NR_AIML_air
Additional study on other aspects of AI/ML model and data
OPPO's study document on AI/ML model identification and data management proposes 9 key technical proposals covering model identification procedures, lifecycle management approaches, and model transfer mechanisms for 3GPP Release 19 NR air…
R1-2410106 RAN1_119 NR_AIML_air
Discussion on LS on applicable functionality reporting for beam management UE-sided model
This OPPO document addresses RAN2's liaison statement on UE-side model inference for beam management, proposing 10 specific answers to technical questions about the 6-step functionality-based lifecycle management procedure. The document…
R1-2410107 RAN1_119 NR_AIML_air
Draft reply on LS on applicable functionality reporting for beam management UE-sided model
This is a liaison statement from RAN1 (OPPO) responding to RAN2's questions about AI/ML beam management UE-sided model functionality reporting for Release 19. The document provides detailed replies to 10 questions covering UE capability…
R1-2410775 RAN1_119 NR_AIML_air
Summary #1 for other aspects of AI/ML model and data
This 3GPP RAN1 document (R1-2410775) from OPPO serves as a moderator summary for AI/ML model and data aspects in Rel-19, containing approximately 20+ proposals across model identification, training data collection, and model…
R1-2410776 RAN1_119 NR_AIML_air
Summary #2 for other aspects of AI/ML model and data
This OPPO-moderated document presents a comprehensive summary of AI/ML model identification, training data collection, and model transfer/delivery discussions for RAN1 #119, containing over 40 proposals across multiple technical areas. The…
R1-2410777 RAN1_119 NR_AIML_air
Summary #3 for other aspects of AI/ML model and data
This OPPO-moderated document (R1-2410777) presents a comprehensive summary for RAN1 agenda item 9.1.4.2 on AI/ML model and data aspects, containing 31 proposals and 15 observations covering model identification procedures, training data…
R1-2410778 RAN1_119 NR_AIML_air
Summary #4 for other aspects of AI/ML model and data
This 3GPP RAN1 technical document from OPPO summarizes discussions on AI/ML model and data aspects for NR air interface, containing approximately 30 proposals across model identification, training data collection, and model…