Spreadtrum · 10.5.2.4
Beam management for downlink and uplink ·
RAN1#124bis · Source verification
the AI's delta
maintained
vs RAN1#124
Same stance on hybrid beamforming as fundamental 6G architecture. Same stance on extending AI/ML beam prediction (BM-Case1 and BM-Case2) to inter-cell/multi-TRP and cross-frequency scenarios. Same stance on studying collaborative beam measurement via UE aggregation to reduce overhead. Minor refinements: added explicit reference to NR beam measurement procedures P1/P2/P3 and U1/U2/U3 as baseline (implicit in prior meeting's NR-centric framing), and added unified flexible beam reporting format proposal accommodating inter-cell, multi-TRP, and UL beam selection jointly considering AI and non-AI content—incrementally more detailed than prior meeting's unified CSI framework language. The earlier explicit inclusion of LTM within the unified framework and the specific mention of low-latency beam measurement schemes are both preserved in substance if not in identical phrasing. No hardened language, no dropped proposals, no new proposal areas.
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Contributions at RAN1#124bis · 1 doc
Discussion on beam management for downlink and uplink for 6GR
Position extracted by AI
Spreadtrum proposes adopting hybrid beamforming as the fundamental 6G architecture and using NR beam measurement procedures (P1/P2/P3, U1/U2/U3) and the NR unified TCI framework as the baseline for 6G design. They propose studying a unified beam management framework that integrates NW-initiated and UE-initiated procedures, single-TRP and multi-TRP, and intra-cell and inter-cell scenarios to avoid the fragmented spec effort seen in NR. For beam reporting, they propose designing a unified and flexible format accommodating inter-cell, multi-TRP, and UL beam selection, jointly considering AI and non-AI content. They propose extending AI/ML beam prediction (BM-Case1 and BM-Case2) to inter-cell/multi-TRP scenarios and cross-frequency prediction, while also studying collaborative beam measurement via UE aggregation to reduce overhead.
Summary
Spreadtrum presents 2 observations and 11 proposals on 6G beam management, arguing NR beam management effectively improves performance but suffers from excessive spec complexity across releases. They propose a unified 6G framework integrating NW-initiated and UE-initiated beam management, enhanced with AI/ML for inter-cell/multi-TRP predictions, while using NR procedures like P1/P2/P3 and unified TCI as a baseline.
Prior contributions at RAN1#124 · 1 doc · Feb 09, 2026
Discussion on beam management for downlink and uplink for 6GR
Position extracted by AI
Spreadtrum proposes hybrid beamforming as the fundamental beamforming architecture for 6G ultra large antenna arrays, supporting digital, analog, and hybrid architectures. They propose studying a unified CSI framework that integrates beam management across network-controlled and UE-initiated cases, single TRP and multi-TRP, and intra-cell and inter-cell scenarios, including LTM. They require studying beam measurement schemes with low latency and overhead, and consider designing a unified event-triggered reporting procedure covering BFR, UE-initiated beam management, and event-triggered TRP/cell switching. They support carrying forward NR BM-Case1 (spatial domain DL Tx beam prediction) and BM-Case2 (temporal DL Tx beam prediction) into 6G, and extending AI/ML beam prediction to inter-cell/multi-TRP and cross-frequency scenarios in 6G Day1. They consider NR's unified TCI framework as the baseline for 6G TCI framework and propose studying collaborative beam measurement and reporting based on UE aggregation to reduce overall overhead and power consumption.
Summary
This Spreadtrum contribution to 3GPP RAN1#124 discusses beam management for 6G Radio, presenting 2 observations on NR beam management effectiveness and standardization complexity, along with 11 proposals covering beamforming architecture, unified CSI frameworks, AI/ML-based beam management, and collaborative UE schemes.
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 Spreadtrum's consolidated stance at RAN1#124bis
against their stance at RAN1#124 and classified the change as
maintained.
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