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Technical meeting summary outlining proposals and discussion points from 3GPP RAN1 #124 regarding inter-vendor training collaboration for AI/ML-based CSI compression, including dataset exchange formats, encoder model structure standardization, pairing mechanisms, and CSI feedback associations within the NR air interface AI/ML phase 2 work item.
Year:
2026
Location:
Gothenburg, Sweden
Event:
3GPP TSG RAN WG1 #124
Dates:
9–13 February 2026
Agenda Item:
9.1.2
Document ID:
R1-2601149
Title:
FL summary #1 for inter-vendor training collaboration
Source:
Moderator (Apple)
Moderator:
Huaning Niu
Organization:
3GPP TSG RAN Working Group 1
Topic:
Artificial Intelligence / Machine Learning for NR air interface
Subtopic:
Inter-vendor training collaboration for two-sided AI/ML models
Technical Scope:
AI/ML-based CSI compression, dataset exchange, model parameter exchange, encoder model structure specification
Related Work Item:
Revised WID “Artificial Intelligence (AI)/Machine Learning (ML) for NR air interface phase 2” (RP-253340)
Participants:
Apple, OPPO, Lenovo, NTT DOCOMO, Huawei, Ericsson, MediaTek, ZTE, CMCC, CATT, Panasonic, NEC, LG Electronics, Fujitsu, vivo, Samsung, Sony, InterDigital, ETRI, TCL, Xiaomi, IITM, Toyota
Document Type:
Technical meeting contribution / summary for discussion and decision
Purpose:
Summary of contributions and proposals discussed under agenda item 9.1.2 in RAN1 #124
Key Topics:
dataset format and exchange, encoder model structure standardization, pairing ID mechanism, CSI feedback and target CSI association
Performance Metrics Mentioned:
SGCS, NMSE
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Year:
2026
Meeting:
3GPP TSG RAN WG1 #124
Document Number:
R1-2601149
Agenda Item:
9.1.2
Location:
Gothenburg, Sweden
Date:
Feb 9–13, 2026
Source:
Moderator (Apple)
Title:
FL summary # 1 for inter-vendor training collaboration
Document For:
Discussion/Decision
Topic:
Inter-vendor training collaboration for two-sided AI/ML models
Related Work Item:
RP-253340 “Revised WID: Artificial Intelligence (AI)/Machine Learning (ML) for NR air interface phase 2”
Technical Scope:
Direction C reference model; Direction A options 3a-1 and 4-1; standardized dataset format/content; encoder model structure; parameter and dataset exchange; CSI compression
Contributing Companies:
Apple, OPPO, Lenovo, NTT DOCOMO, Huawei, HiSilicon, Ericsson, MediaTek, ZTE, CMCC, CATT, Panasonic, NEC, LG Electronics, Fujitsu, vivo, Samsung, Sony, InterDigital, ETRI, TCL, Xiaomi, IITM, Toyota
Contact Persons:
Huaning Niu; Wendong Liu; Vahid Pourahmadi; Xin Wang; Keyvan Zarifi; Yuan Li; Jingya Li; Xinlin Zhang; Pedram Kheirkhah Sangdeh; Reubengeorge Stephen; Hanchao Liu; Wenfeng Liu; Yi Zheng; Yongchang Liu; Qianrui Li; Tetsuya Yamamoto; Hidetoshi Suzuki; Xuan Tuong Tran; Shafivulla Sayyed; Peng Guan; Zhen He; Minseok Jo; Xin Wang; Liqiang Jin; Yuanyuan Wang; Ameha Tsegaye Abebe; Chen Sun; Yingshuang Bai; Afshin Haghighat; Anseok Lee; Pu Yuan; Tianqi Wu; Mu Qin; Liu Zhengxuan; Liu Min; Anil Kumar Y; Sai Praneeth K; Konstantinos Dimou; Takayuki Shimizu
Performance Metrics:
Average SGCS; Average NMSE; Optional NMSE and/or SGCS at X-percentiles
Open Issues:
Pairing ID uniqueness; impact of additional dataset samples; quantization codebook exchange method; rank association; per-layer CSI payload size consistency
Year:
2026
Region / city:
Gothenburg, Sweden
Topic:
Artificial Intelligence (AI) / Machine Learning (ML) for NR air interface
Document Type:
Technical Report
Organization:
3GPP TSG RAN WG1
Author:
Moderator (Apple)
Target Audience:
Industry professionals and organizations in telecommunications
Effective Period:
2026-02-09 to 2026-02-13
Approval Date:
February 9th, 2026
Last Modified:
February 13th, 2026
Year:
2026
Location:
Gothenburg, Sweden
Organization:
3GPP TSG RAN WG1
Meeting:
RAN WG1 #124
Agenda Item:
9.1.2
Document ID:
R1-2601149
Title Reference:
FL summary #1 for inter-vendor training collaboration
Source:
Moderator (Apple)
Primary Contact:
Huaning Niu
Companies Involved:
Apple, OPPO, Lenovo, NTT DOCOMO, Huawei, HiSilicon, Ericsson, MediaTek, ZTE, China Mobile, CATT, Panasonic, NEC, LG Electronics, Fujitsu, vivo, Samsung, Sony, InterDigital, ETRI, TCL, Xiaomi, IITM, Toyota, Ofinno, Spreadtrum
Technical Domain:
AI/ML for NR air interface
Subject:
Inter-vendor training collaboration for AI/ML-based CSI compression
Related Work Item:
Artificial Intelligence (AI)/Machine Learning (ML) for NR air interface phase 2 (RP-253340)
Document Type:
Technical meeting contribution summary
Purpose:
Discussion and decision
Technical Scope:
Dataset exchange, encoder model structure, model parameter exchange, CSI feedback and target CSI association
Participants:
Multiple telecommunications vendors and research organizations
Contact Information Included:
Yes
Year:
2026
Region / City:
Gothenburg, Sweden
Topic:
Artificial Intelligence (AI) / Machine Learning (ML)
Document Type:
Meeting Document
Organization / Institution:
3GPP TSG RAN WG1
Author:
Moderator (Apple), Huaning Niu, et al.
Target Audience:
3GPP TSG RAN WG1 members, vendors
Period of Validity:
2026
Approval Date:
February 2026
Date of Changes:
N/A
Contact Information:
[email protected], [email protected], etc.
Summary:
The document summarizes proposals and contributions regarding inter-vendor AI/ML-based training collaboration within the context of the 3GPP RAN1 #124 meeting.
Year:
2015
Region / City:
London, UK
Topic:
Fetal and neonatal echocardiography
Document Type:
Research Article
Authors:
Dr. Olga Patey, Professor Julene S. Carvalho, Professor Basky Thilaganathan
Target Audience:
Medical professionals, researchers
Period of Study:
2012–2015
Approval Date:
2012
Modification Date:
Not specified
Keywords:
fetal heart, fetal echocardiography, myocardial deformation, neonatal echocardiography, speckle tracking, tissue Doppler imaging, repeatability, reproducibility
Context Description:
The document evaluates the inter-vendor reproducibility and observer repeatability of TDI and STE measurements in normal term fetuses and neonates, emphasizing the challenges in comparing echocardiographic findings across different ultrasound systems.
Year:
2026
Region / City:
Gothenburg, Sweden
Topic:
AI/ML Inter-vendor Collaboration
Document Type:
Report
Organization:
3GPP
Author:
Moderator (Apple), Huaning Niu
Target Audience:
Industry professionals in AI/ML and 3GPP members
Action Period:
February 9th - 13th, 2026
Approval Date:
Not specified
Date of Changes:
Not specified
Note:
Summary
Year:
2026
Region / City:
Gothenburg, Sweden
Theme:
AI/ML in NR air interface
Document Type:
Discussion/Decision
Organization / Institution:
3GPP TSG RAN WG1
Author:
Huaning Niu (Apple), Wendong Liu (OPPO), Vahid Pourahmadi (Lenovo), Xin Wang (NTT DOCOMO), Keyvan Zarifi (Huawei), et al.
Target Audience:
Industry professionals in wireless communications and AI/ML
Period of Application:
2026
Approval Date:
February 9th – 13th, 2026
Date of Changes:
Not specified
Year:
2026
Region / City:
Gothenburg, Sweden
Topic:
Inter-vendor AI/ML training collaboration
Document Type:
Meeting Summary
Organization:
3GPP TSG RAN WG1
Author:
Moderator (Apple)
Target Audience:
3GPP Members
Period of Validity:
February 9th – 13th, 2026
Approval Date:
N/A
Modification Date:
N/A
Year:
2026
Location:
Gothenburg, Sweden
Subject:
AI/ML-based inter-vendor training collaboration for NR air interface
Document Type:
Meeting summary / technical report
Organization:
3GPP TSG RAN WG1
Authors:
Moderator (Apple), Huaning Niu; contributions from OPPO, Lenovo, NTT DOCOMO, Huawei, Ericsson, MediaTek, ZTE, CMCC, CATT, Panasonic, NEC, LG Electronics, Fujitsu, vivo, Samsung, Sony, InterDigital, ETRI, TCL, Xiaomi, IITM, Toyota, Ofinno, Spreadtrum, China Telecom, Futurewei
Agenda Item:
9.1.2
Reference:
RP-253340, Revised WID: Artificial Intelligence (AI)/Machine Learning (ML) for NR air interface phase 2
Key Topics:
Direction C reference model, Direction A sub-options 3a-1 and 4-1, standardized dataset and parameter exchange, performance metrics (SGCS/NMSE), RAN1 scalability study outcomes
Meeting Dates:
Feb 9–13, 2026
Contact Emails:
[email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected]
Year:
2026
Location:
Gothenburg, Sweden
Subject:
AI/ML inter-vendor training collaboration for NR air interface
Document type:
Meeting report / Summary
Organization:
3GPP TSG RAN WG1
Authors:
Huaning Niu (Apple), Wendong Liu (OPPO), Vahid Pourahmadi (Lenovo), Xin Wang (NTT DOCOMO), Keyvan Zarifi & Yuan Li (Huawei, HiSilicon), Jingya Li & Xinlin Zhang (Ericsson), Pedram Kheirkhah Sangdeh & Reubengeorge Stephen (MediaTek), Hanchao Liu & Wenfeng Liu (ZTE), Yi Zheng & Yongchang Liu (CMCC), Qianrui Li (CATT), Tetsuya Yamamoto, Hidetoshi Suzuki & Xuan Tuong Tran (Panasonic), Shafivulla Sayyed, Peng Guan & Zhen He (NEC), Minseok Jo (LG Electronics), Xin Wang & Liqiang Jin (Fujitsu), Yuanyuan Wang (vivo), Ameha Tsegaye Abebe (Samsung), Chen Sun & Yingshuang Bai (Sony), Afshin Haghighat (InterDigital), Anseok Lee (ETRI), Pu Yuan & Tianqi Wu (TCL), Mu Qin, Liu Zhengxuan & Liu Min (Xiaomi), Anil Kumar Y & Sai Praneeth K (IITM), Konstantinos Dimou & Takayuki Shimizu (Toyota), Jaehoon Chung (Ofinno), Zhe Yu (Spreadtrum), Nanxi Li & Yueyan Chu (China Telecom), Baoling Sheen (Futurewei)
Agenda item:
9.1.2
Period:
Feb 9–13, 2026
Source:
Moderator (Apple)
Status:
Discussion/Decision
Focus:
Specification of standardized dataset format/content, parameter exchange, RAN1 scalability, AI/ML CSI compression models
Year:
2026
Location:
Gothenburg, Sweden
Subject:
AI/ML-based NR air interface inter-vendor training
Document type:
Meeting summary / Technical contribution
Organization:
3GPP TSG RAN WG1
Author:
Moderator (Apple), Huaning Niu
Participants:
Apple, OPPO, Lenovo, NTT DOCOMO, Huawei, Ericsson, MediaTek, ZTE, CMCC, CATT, Panasonic, NEC, LG Electronics, Fujitsu, vivo, Samsung, Sony, InterDigital, ETRI, TCL, Xiaomi, IITM, Toyota, Ofinno, Spreadtrum, China Telecom, Futurewei
Agenda item:
9.1.2
Period:
Feb 9–13, 2026
Topics covered:
Standardized dataset format, model parameter exchange, Direction A 3a-1 and 4-1, Direction C reference model, RAN1 scalability study outcomes, inter-vendor AI/ML collaboration agreements
Contact emails:
Provided for all participating companies
Year:
2026
Region / City:
Gothenburg, Sweden
Topic:
Inter-vendor training collaboration in AI/ML models for NR air interface
Document Type:
Meeting Agenda
Organization / Institution:
3GPP TSG RAN WG1
Author:
Moderator (Apple), Huaning Niu
Target Audience:
3GPP participants, RAN1, RAN4 experts
Period of Validity:
February 9th – 13th, 2026
Approval Date:
February 9th, 2026
Date of Changes:
N/A
Year:
2021
Standardization body:
3GPP
Working group:
TSG-RAN WG1
Meeting:
RAN1 #104-e eMeeting
Dates:
January 25 – February 5, 2021
Agenda item:
8.16
Subject:
Introduction of 1024-QAM for NR downlink in FR1
Document type:
Technical discussion summary
Document purpose:
Discussion and decision
Source:
Moderator (Ericsson)
Technology:
NR (5G)
Frequency range:
FR1
Key topics:
CQI tables, MCS tables, 1024-QAM modulation, RRC configuration, DCI formats
Related specifications:
LTE CQI tables, NR 256-QAM MCS tables
Contributing organizations:
vivo, CATT, Intel, Huawei, HiSilicon, ZTE, Sanechips, Nokia, NSB, Samsung
Decisions status:
Proposals under discussion
Meeting:
3GPP TSG RAN WG1 #100bis
Date:
April 20–30, 2020
Source:
moderator (vivo)
Document type:
Meeting contribution / feature lead summary
Agenda item:
7.2.6.4
Purpose:
Discussion and Decision
Subject:
Rel-16 UL full power transmission capability and UE capability reporting
Contains:
company comments on proposed technical proposals and specification alignment
Referenced specifications:
TS 38.331, TS 38.213, TS 38.214, TS 38.306
Key issue:
applicability of Rel-16 UL full power TX and codebook subset for coherent and non-coherent UE
Companies commenting:
OPPO, Samsung, CATT, Apple, Huawei/HiSilicon, ZTE, LG, Intel, Spreadtrum
Year:
2023
Meeting:
3GPP TSG RAN WG1 Meeting #114
Location:
Toulouse, France
Dates:
21 August 2023 – 25 August 2023
Source:
Moderator (Intel Corporation)
Agenda item:
9.5.1.1
Document for:
Discussion and Decision
Subject:
SL positioning reference signal (SL PRS)
Release:
Rel-18
Working Item:
Expanded and improved NR positioning
Related groups:
RAN1, RAN2, RAN3, RAN4
Frequency ranges:
FR1, FR2
Organizations mentioned:
OPPO; CATT; Intel Corporation
Document Type:
Meeting Report
Organization:
3GPP TSG RAN WG1
Date:
August 17–28, 2020
Reference ID:
R1-200abcd
Scope:
CSI enhancements for MTRP and FR1 FDD reciprocity
Frequency Range:
FR1
Duplex Mode:
FDD
Scenario:
Dense Urban Macro
Antenna Configuration:
gNB 16–32 ports, UE 2–4 RX
Evaluation Metrics:
Throughput and CSI feedback overhead
MIMO Scheme:
SU-MIMO / MU-MIMO with rank adaptation
Channel Modeling:
FDD DL/UL reciprocity, Options 1 and 2
Companies Participating:
19 companies including VIVO, Samsung, Ericsson, Nokia, Apple, Huawei/HiSi
Year:
2020
Region / city:
Electronic meeting
Topic:
5G, UE capabilities
Document type:
Change Request
Organization / institution:
3GPP
Author:
Intel Corporation, NTT DOCOMO, INC.
Target audience:
3GPP Working Group members
Period of validity:
June 01 - 12, 2020
Approval date:
2020-06-01
Revision date:
2020-06-01
Release:
Rel-16
Category:
B (addition of feature)
Reason for change:
Capture UE capabilities based on RAN1 UE feature list
Clauses affected:
To be added
Other affected specifications:
TS/TR 38.306
Other comments:
None
Year:
2022
Meeting:
3GPP TSG RAN WG1 Meeting #110bis-e
Meeting dates:
Oct 10–19, 2022
Document number:
R1-22xxxxx
Agenda item:
9.5
Document for:
Discussion
Title:
Comments to Draft TR 38.859 v020: Study on expanded and improved NR positioning
Source:
Intel Corporation, CATT, Ericsson
Related document:
R1-2210233
Technical specification:
TR 38.859
Working group:
3GPP TSG RAN WG1
Subject:
Study on expanded and improved NR positioning
Format references:
.docx, spreadsheet checkout procedure
Time reference:
UTC
Contributing companies:
Open to participating companies
Collaborative procedure:
Version control and checkout file mechanism
Year:
2022
Location:
Toulouse, France
Meeting:
3GPP TSG RAN WG1 Meeting #110
Working Group:
RAN1
Agenda Item:
9.7.2
Document Type:
Discussion Contribution
Document For:
Discussion
Source:
Moderator (Intel Corporation)
Title Reference:
Discussion Summary #1 for energy saving techniques of NW energy saving SI
Related Work Item:
RP-220297
Scope:
Study on network energy saving for NR including base station energy consumption model, evaluation methodology and KPIs
Technical Areas:
Network energy saving, base station energy consumption modeling, evaluation methodology, KPIs, time-domain energy saving techniques, gNB and UE coordination
Frequency Ranges:
FR1, FR2
Deployment Scenarios:
Urban micro, Urban/Rural macro, EN-DC/NR-DC, single-carrier and multi-carrier deployments
Completion Target:
End of 2022
Participating Companies Mentioned:
Intel Corporation, Nokia, NSB, Fraunhofer IIS, Fraunhofer HHI, Futurewei, Huawei, Spreadtrum Communications
Year:
2022
Region / City:
Global
Topic:
Wireless communication; CSI reporting enhancements
Document Type:
Meeting report / Technical specification proposal
Organization:
3GPP TSG RAN WG1
Author:
Huawei, HiSilicon (Moderator)
Audience:
RAN1 working group members and participating companies
Meeting Dates:
February 21 – March 3, 2022
Agenda Item:
8.1.4
Proposals:
Further enhancement, correction, editorial changes
Target Release:
Rel-17
Frequency Range:
FR1, FR2
Technologies:
MTRP, FDD, CSI-RS, Type II port selection
Companies Contributing:
Lenovo, Samsung, Vivo, CATT