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Summary #1 of specification support for positioning accuracy enhancement
This 3GPP RAN1 meeting summary document (R1-2410714) from Ericsson covers AI/ML for NR Air Interface positioning accuracy enhancement, containing over 90 proposals and conclusions across 8 major sections covering model input, output, training data collection, inference, and…
Ericsson advocates FOR: (1) Supporting both sample-based and path-based measurements as compromise solution to enable progress, (2) Reusing existing legacy IEs and frameworks wherever possible to minimize specification impact, (3)…
Summary #2 of specification support for positioning accuracy enhancement
This document contains approximately 15 proposals and 2 conclusions from Ericsson covering AI/ML positioning enhancements including sample-based vs path-based measurements, LOS/NLOS indicators for model output, training data collection procedures, and model inference consistency…
Ericsson advocates FOR: (1) supporting both sample-based and path-based measurements as a compromise solution to avoid blocking progress, (2) reusing existing legacy IEs and signaling frameworks wherever possible to minimize specification…
Summary #3 of specification support for positioning accuracy enhancement
This document is RAN1#119 Summary #3 from Ericsson covering AI/ML positioning accuracy enhancement with approximately 120+ proposals/conclusions across model input, output, training data collection, inference, and monitoring. The document extensively discusses sample-based vs…
Ericsson as document moderator presents a balanced compromise approach, advocating FOR: (1) supporting both sample-based and path-based measurements to avoid blocking progress despite company divisions, (2) reusing existing signaling…
Summary #4 of specification support for positioning accuracy enhancement
This 3GPP RAN1 document (Tdoc R1-2410717) from Ericsson summarizes discussions on AI/ML-based positioning accuracy enhancements from RAN1#119, containing over 80 proposals across model input definitions, output specifications, training data collection, and model inference…
Ericsson advocates FOR sample-based measurements over path-based measurements, supporting flexible parameter configurations (Nt, Nt', k) while maintaining backward compatibility with legacy positioning methods. They push FOR reusing…
Summary #5 of specification support for positioning accuracy enhancement
This RAN1 document from Ericsson presents 95 proposals across 6 major technical areas for AI/ML-based positioning enhancement in NR, covering model input definitions, model output specifications, training data collection, inference procedures, and performance monitoring…
Ericsson advocates FOR sample-based measurements as the primary approach for AI/ML positioning input (supporting majority view over compromise approaches), FOR reusing existing legacy signaling frameworks and IEs where possible to minimize…
Summary#1 of Additional study on AI/ML for NR air interface: CSI compression
This technical document from Qualcomm serves as a moderator summary for additional study on AI/ML-based CSI compression for NR air interface, containing over 120 proposals from various companies across temporal domain aspects, localized models, inter-vendor training…
Qualcomm, as the moderator, advocates FOR prioritizing temporal domain Cases 2 and 3 with separate prediction and compression as baseline, supporting Direction A (dataset sharing via option 4-1) combined with Direction C for inter-vendor…
Summary#2 of Additional study on AI/ML for NR air interface: CSI compression
This 3GPP RAN1 technical document (Tdoc R1-2410720) presents a draft summary of AI/ML-based CSI compression studies, containing over 300 proposals from various companies covering temporal domain aspects, inter-vendor training collaboration, monitoring, and inference aspects. The…
Qualcomm, as the document moderator, advocates for prioritizing Direction A Option 4-1 (dataset exchange) for inter-vendor collaboration while supporting Direction C for minimum performance assurance. They push for dataset sharing over…
Summary#3 of Additional study on AI/ML for NR air interface: CSI compression
This 3GPP RAN1 technical document (R1-2410721) from Qualcomm serves as the draft summary for AI/ML-based CSI compression study, containing over 100 company proposals across temporal domain aspects, inter-vendor collaboration, monitoring, and inference aspects. The document…
Qualcomm, as the moderator, advocates FOR: (1) Prioritizing Direction A Option 4-1 (dataset exchange) over Option 3a-1 due to lower specification complexity while maintaining performance, (2) Supporting Direction C for minimum performance…
Summary#4 of Additional study on AI/ML for NR air interface: CSI compression
This 3GPP RAN1 technical document (Tdoc R1-2410722) from Qualcomm presents a comprehensive draft summary on AI/ML for NR air interface CSI compression, containing approximately 120+ proposals across four major sections covering temporal domain aspects, localized models,…
Qualcomm, as the moderator, advocates FOR prioritizing Case 2 and Case 3 temporal domain aspects with separate prediction and compression as baseline, supporting Direction A Option 4-1 (dataset exchange) over Option 3a-1 (parameter…
Summary#5 of Additional study on AI/ML for NR air interface: CSI compression
This 3GPP RAN1 document from Qualcomm presents a comprehensive summary of AI/ML-based CSI compression study results with over 100 proposals from multiple companies covering temporal domain aspects, inter-vendor training collaboration, monitoring, and data collection. The…
Qualcomm, as the moderator, advocates for a balanced approach prioritizing Direction A Option 4-1 (dataset exchange) for inter-vendor collaboration while maintaining Direction C (fully specified models) as a minimum performance baseline.…
Final summary of Additional study on AI/ML for NR air interface: CSI compression
This 3GPP RAN1 document (R1-2410724) from Qualcomm serves as the final meeting summary for AI/ML-based CSI compression studies in Release 19, containing over 200 proposals from multiple companies across temporal domain aspects, inter-vendor collaboration, monitoring, and data…
Qualcomm, as the document moderator, advocates for a pragmatic approach prioritizing Direction A Option 4-1 (dataset sharing) over Option 3a-1 due to lower specification complexity, while supporting Direction C as a minimum performance…
Updated summary of Evaluation Results for AI/ML CSI compression
This document from Qualcomm presents comprehensive evaluation results for AI/ML based CSI compression in NR air interface, containing 16 main observations across different test cases covering SGCS performance, FTP traffic, full buffer scenarios, CSI feedback reduction, and…
Qualcomm, as the moderator, is advocating for comprehensive standardization of AI/ML based CSI compression techniques across multiple scenarios and configurations. They are pushing FOR detailed performance characterization across different…
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 UE-side and network-side models for both…
Samsung advocates for a flexible framework combining multiple options for UE-side model applicability (merging Options 1 and 2), supports dedicated monitoring configurations separate from inference configurations, and pushes for practical…
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 inference reporting. The document addresses…
Samsung advocates for a flexible approach supporting multiple options for UE-sided model applicability reporting, favoring dedicated monitoring configurations separate from inference configurations, and supporting enhanced quantization…
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, configuration methods, inference reporting, and…
Samsung advocates for a comprehensive framework supporting both UE-side and NW-side AI/ML models with emphasis on: 1) Flexible applicability reporting combining multiple options rather than forcing single approach, 2) Dedicated 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 reporting, and beam indication frameworks.
Samsung, as the document moderator, advocates for: (1) merging applicability options to give RAN2 flexibility in container design while supporting both CSI-ReportConfig and inference parameter approaches, (2) comprehensive performance…
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 monitoring, data collection, and beam…
Samsung advocates for practical AI/ML beam management implementations that reuse existing CSI frameworks while introducing minimal spec impact. They push FOR: reusing legacy CSI-ReportConfig structures, supporting both UE-side and NW-side…
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 transfer/delivery. The document consolidates company…
OPPO, as the moderator, is advocating FOR a systematic study of model identification mechanisms for two-sided models, particularly supporting MI-Option2 with dataset transfer and standardized model structures for Case z4. They push FOR…
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 document addresses three main topics:…
OPPO, as document moderator, advocates for a balanced approach supporting both functionality-based and model ID-based LCM operations while prioritizing standardized model structures over offline vendor collaboration. They push FOR unified…
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 transfer/delivery topics. The document focuses on…
OPPO, as the moderator, is advocating FOR a unified approach to AI/ML model identification that supports both functionality-based and model-ID-based operations, with network-assigned model IDs preferred for consistency. They push FOR…
Summary #1 of CSI prediction
This 3GPP RAN1 document from LG Electronics summarizes CSI prediction evaluation results and consistency issues between training and inference for UE-sided AI/ML models. The document contains numerous observations from multiple companies regarding generalization performance…
LG Electronics, as the moderator, takes a consensus-building approach advocating for concluding that tilt angle and TXRU mapping have negligible impact on CSI prediction generalization performance based on majority company results. They…
Summary #2 of CSI prediction
This 3GPP RAN1 technical document from LG Electronics presents a comprehensive summary of CSI prediction discussions covering consistency between training and inference, with over 100 observations and proposals from multiple companies. The document focuses on evaluating whether…
As the document moderator, LG Electronics takes a balanced approach by summarizing industry consensus rather than advocating for specific technical solutions. They facilitate the discussion toward concluding that tilt angle has negligible…
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 multiple technical issues.
Samsung, as the moderator, advocates for a comprehensive AI/ML beam management framework supporting both UE-sided and NW-sided models with practical implementation considerations. They push for flexible configuration options (supporting…
Summary #3 of CSI prediction
This 3GPP RAN1 document (R1-2410899) from LG Electronics summarizes evaluation results for AI/ML based CSI prediction, focusing on consistency between training and inference regarding network-side conditions like antenna tilt angles and TXRU mapping. The document contains…
LG Electronics, as the document moderator, presents a comprehensive summary showing mixed industry consensus on CSI prediction consistency issues. They advocate for concluding that antenna tilt angles have negligible impact and don't…
Final summary of specification support for positioning accuracy enhancement
This 3GPP RAN1 document (R1-2410921) from Ericsson presents a final summary of discussions on AI/ML for NR Air Interface positioning accuracy enhancement from RAN1#119 meeting. The document contains over 160 proposals and conclusions across model input/output, training data…
Ericsson advocates FOR sample-based measurements as an enhancement to legacy path-based reporting, supporting both alternatives to avoid blocking progress while preferring sample-based for better AI/ML positioning performance. They push…