Company
Samsung
13 contributions across 1 work items
13
Tdocs
1
Work items
Recent position changes
AI-synthesized from contributions · all text is paraphrased
New positions this meeting
- 9.1.1 — Advocates for a comprehensive framework supporting both network-side and UE-side models with flexible configuration options, separate CPU counting for AI/ML vs legacy CSI reports, and enhanced signaling mechanisms.
- 9.1.2 — Advocates for a comprehensive AI/ML positioning framework that balances performance with overhead reduction, supporting flexible data collection approaches and UE autonomy in data provider decisions.
- 9.1.3 — Strongly advocates for network-assisted AI/ML model training consistency with TRP-related signaling, emphasizing critical need to address severe performance degradation from antenna configuration mismatches.
- 9.1.4.1 — Strongly advocates for angle-delay (W2) domain compression over spatial-frequency (W) domain compression due to superior generalizability, and pushes for temporal aspects in CSI compression (Cases 2 and 3) with specific focus on basis vector refresh.
- 9.1.4.2 — Advocates for simplified model identification approaches that avoid complex cross-vendor collaboration, supporting network-side additional condition indicators, standardized reference models (MI-Option 4), and restricting data collection to 3GPP network entities.
Recent contributions
Discussion for supporting AI/ML based beam management
Samsung presents 30 proposals and 1 observation regarding AI/ML-based beam management for NR, covering both NW-side and UE-side models. The document addresses data collection for training and inference, spatial and temporal enhancements…
Discussion for supporting AI/ML based positioning accuracy enhancement
Samsung presents a comprehensive discussion on AI/ML-based positioning accuracy enhancement, outlining 29 observations across triggering, model selection, data collection, inference, monitoring, and consistency checks. The document…
Views on AI/ML based CSI prediction
Samsung presents observations and proposals for AI/ML-based CSI prediction in NR, highlighting the performance degradation when models are trained on mismatched TRP antenna settings and the need for network assistance to ensure…
Views on additional study for AI/ML based CSI compression
Samsung presents views on further studies for AI/ML-based CSI compression in Rel-19, focusing on temporal aspects (Case 2 and Case 3), performance-complexity trade-offs, and inter-vendor training collaboration. The document contains 18…
Views on additional study for other aspects of AI/ML model and data
Samsung analyzes model identification and data handling for AI/ML in NR, presenting 13 proposals and 5 observations across model-level management, two-sided model consistency, and data privacy. The document argues that explicit model…
FL summary #0 for AI/ML in beam management
This Samsung-moderated 3GPP RAN1 document (Tdoc R1-2410733) presents a comprehensive summary of AI/ML beam management contributions from meeting #118, containing over 100 proposals across multiple technical areas. The document covers…
FL summary #1 for AI/ML in beam management
This Samsung-moderated FL summary document for RAN1#119 contains over 250 proposals and observations across 9 main sections covering AI/ML beam management, including RAN2 LS handling, performance monitoring, configuration aspects, and…
FL summary #2 for AI/ML in beam management
This 3GPP RAN1 technical document (Tdoc R1-2410735) from Samsung serves as FL summary #2 for AI/ML in beam management, containing over 200 proposals and observations across multiple technical areas including performance monitoring,…
FL summary #3 for AI/ML in beam management
This document is Samsung's FL summary #3 for AI/ML in beam management from RAN1 #119, containing over 40 proposals and observations covering UE-side and NW-side model configurations, performance monitoring, data collection, inference…
FL summary #4 for AI/ML in beam management
This is Samsung's summary document (R1-2410737) for AI/ML in beam management from RAN1 #119 meeting, containing over 200 proposals and observations from multiple companies covering UE-side and NW-side model configurations, performance…
FL summary #5 for AI/ML in beam management
This is Samsung's FL summary #5 for AI/ML in beam management (Tdoc R1-2410892), containing over 100 proposals addressing UE-sided and NW-sided models, performance monitoring, configuration frameworks, and beam indication mechanisms across…
[DRAFT] Reply LS on applicable functionality reporting for beam management UE-sided model
This is a liaison statement from RAN1 to RAN2 responding to questions about beam management UE-sided AI/ML model functionality reporting. The document provides answers to 9 detailed questions and includes 2 agreements and 1 conclusion…
Reply LS on applicable functionality reporting for beam management UE-sided model
Samsung's response to RAN2's liaison statement regarding applicable functionality reporting for beam management UE-sided AI/ML models, containing 4 key observations about terminology definitions and 3 agreements/conclusions on…