Nokia · 10.5.2.4
Beam management for downlink and uplink ·
RAN1#124bis · Source verification
the AI's delta
refined
vs RAN1#124
Refined QCL framework position: added proposal for flexible QCL parameterization allowing per-RS configuration of channel properties instead of fixed QCL types—a more detailed alternative to prior meeting's general enhancements to address identified limitations.' Added explicit proposal to reduce reliance on periodic TRS as main QCL source to improve energy efficiency, previously framed as limitations without this specific remedy. Refined AI/ML beam prediction scope: prior meeting proposed studying cross-frequency beam prediction generally; current meeting grounds it as direct extension of Rel-19 BM-case1/BM-case2 and adds new cross-frequency simulation results showing 2-3 dB mean RSRP error for UEs below -80 dBm, complementing prior meeting's inter-cell Top-1/Top-2 accuracy results. Narrowed UE-initiated reporting to Rel-19 Event-2 and Event-7 as baseline with BFR-type signaling as fallback, replacing prior meeting's broader unified design for UE-initiated L1 measurement reporting framework across BM and beam-based cell switch framing. Dropped the explicit argument that beam is non-descriptive and should be replaced with RS-based procedures. Dropped CFRA-based BFR study proposal, retaining only CBRA-based BFR with MAC CE as baseline.
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Contributions at RAN1#124bis · 1 doc
On beam management for downlink and uplink in 6GR
Position extracted by AI
Nokia proposes a unified 6GR beam management framework based on 5G NR Rel-17 unified TCI principles, while studying enhancements to address identified limitations. They propose studying a more flexible QCL parameterization that allows per-RS configuration of channel properties instead of fixed QCL types, and reducing reliance on periodic TRS as the main QCL source to improve energy efficiency. For AI/ML beam prediction, they position 5G NR Rel-19 spatial domain (BM-case1) and temporal domain (BM-case2) DL Tx beam prediction as the starting point, and propose direct extensions for inter-cell/multi-TRP and cross-frequency beam prediction. They propose studying UE-initiated beam reporting based on 5G NR Rel-19 Event-2 and Event-7, and studying BFR-type signaling as a fallback mechanism, with CBRA-based BFR using MAC CE signaling as the baseline. For evaluation, they provide simulation results showing inter-cell beam prediction achieving over 90% Top-1 beam ID accuracy and cross-frequency beam prediction achieving 2-3 dB mean RSRP error for UEs below -80 dBm.
Summary
Nokia's Tdoc R1-2601838 proposes a comprehensive study for 6G Radio Layer 1 beam management, presenting 21 proposals and 16 observations. The document addresses the QCL/TCI framework, downlink and uplink beam measurement/reporting with AI/ML enhancements, beam indication, beam failure recovery, and evaluation methodology.
Prior contributions at RAN1#124 · 1 doc · Feb 09, 2026
On beam management for downlink and uplink in 6GR
Position extracted by AI
Nokia proposes that the NR Release-17 unified TCI framework principles serve as the baseline for 6G beam management, while studying enhancements to address identified limitations including the limited number of indicated TCI states, reliance on periodic TRS as QCL source RS, and lack of TCI-state specific physical-layer parameter configuration. They propose a unified design for UE-initiated L1 measurement reporting framework across beam management and beam-based cell switch procedures, citing fragmentation between RAN1-led UEIBR (UCI-based) and RAN2-led LTM event-triggered reporting (MAC CE-based) as a key lesson from 5G NR. Nokia argues that the term "beam" is non-descriptive and potentially misleading for specifications and should be replaced with procedures reflecting the involved reference signals. They propose studying CBRA-based BFR with MAC CE signaling as the baseline, while also studying streamlined CFRA-based BFR and UL beam failure recovery within a unified TCI state framework. For AI/ML, Nokia presents simulation results for inter-cell beam prediction showing Top-1 beam ID accuracy exceeding 90% and Top-2 approaching 99%, and proposes studying cross-frequency beam prediction using one-sided AI/ML models for collocated deployments predicting beams across different component carriers within the same frequency range.
Summary
Nokia presents 17 proposals and 15 observations on 6G beam management, advocating for a unified TCI framework as the baseline while addressing 5G NR limitations. The document covers beam indication, reporting, failure recovery, inter-cell operation, QCL simplification, and AI/ML use cases including inter-cell, beam pair, and cross-frequency prediction.
How this was derived
The AI extracted the "position extracted" field above directly from each Tdoc during summarization.
For the delta summary at the top, the AI compared Nokia's consolidated stance at RAN1#124bis
against their stance at RAN1#124 and classified the change as
refined.
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