Kyocera Corporation · 10.5.2.4
Beam management for downlink and uplink ·
RAN1#124bis · Source verification
the AI's delta
shifted
vs RAN1#124
Shifted baseline stance: prior meeting proposed reusing Rel-18/19 inter-cell AI/ML BM framework for D-MIMO; current meeting adopts Rel-17/18 unified TCI framework and QCL rules as baseline without redesign, broadening the foundation. Added new proposal to study streamlined QCL chain design evaluating removal or reduction of UE-specific periodic TRS as QCL source RS, explicitly assessing impacts on tracking robustness, system performance, and overhead—no such QCL-chain critique appeared before. Dropped earlier emphasis on Set A/Set B mechanism reuse for TRP selection and the specific L1-RSRP N=6 or 8 limitation argument for joint transmission scheduling. Added new event-driven UEIBM UL reporting framework proposal eliminating Events 1, 2, 3, 9 as redundant, modifying Event-5 to support mTRP dynamic switching between DPS and CJT modes, and specifying aperiodic UL procedure with conditional network response—substantially more detailed than prior meeting's general temporal beam prediction extension to D-MIMO. Added study of associated ID limitations including potential disclosure of NW proprietary information, not previously discussed.
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Contributions at RAN1#124bis · 1 doc
Beam management for downlink and uplink
Position extracted by AI
Kyocera proposes adopting the Rel-17/18 unified TCI framework and existing QCL rules as the baseline for 6GR beam indication without redesign. They propose studying a streamlined QCL property/chain design that evaluates removing or reducing reliance on UE-specific periodic TRS as a QCL source RS, explicitly assessing impacts on tracking/channel estimation robustness, system performance, and overhead/energy consumption. They propose studying low-latency beam indication mechanisms including prediction-assisted methods realizable with AI/ML and non-AI approaches to reduce beam update latency in high-mobility and dense mTRP deployments. For AI/ML beam management, they propose studying methods to address associated ID limitations including potential disclosure of NW proprietary information across sTRP and mTRP scenarios. For UEIBM, they propose eliminating Events 1, 2, 3, and 9 as redundant, and modifying Event-5 to support mTRP dynamic switching between DPS and CJT modes where the UE reports a group of M TRPs meeting quality conditions. They propose studying and specifying an event-driven UEIBM UL reporting framework with aperiodic UL procedure and conditional network response only when beneficial.
Summary
Kyocera's R1-2601879 contribution for 6GR beam management presents 11 proposals and 8 observations covering simulation assumptions, QCL/beam indication, beam measurement/report, and UE-initiated beam management (UEIBM), advocating for a unified TCI/QCL framework baseline, simplified QCL chains, enhanced mTRP and inter-cell signaling, and a refined event-driven UEIBM procedure with conditional network response.
Prior contributions at RAN1#124 · 1 doc · Feb 09, 2026
Beam Management for Multi-TRP transmission in 6GR
Position extracted by AI
Kyocera proposes reusing the Rel-18/19 inter-cell AI/ML beam management framework for Distributed MIMO (D-MIMO) scenarios with multi-TRP transmission. They propose using 5G NR 2-TRP operation as a baseline reference and studying m-TRP operation with more than 2 TRPs, documenting throughput gains versus complexity increase. They propose studying spatial domain beam prediction to reduce the number of searches and processing time across multiple TRP beam candidates, specifically reusing the Set A / Set B mechanism from Rel-18/19 for efficient TRP selection based on UE measurement reports. They propose extending temporal-domain beam prediction to D-MIMO to improve beam tracking and enable seamless TRP switching for mobile UEs. They propose studying beam management for multiple TRP deployments that considers multiple UEs connecting to multiple TRPs simultaneously, and specifically studying efficiency improvements for CSI-RS reporting in D-MIMO, noting that current L1-RSRP reporting limits of N = 6 or 8 may provide insufficient prediction accuracy for joint transmission scheduling with multiple TRPs and UEs.
Summary
Kyocera presents 5 proposals for AI-based beam management for multi-TRP transmission in 6G, arguing that Rel-18/19 AI/ML frameworks should be reused and extended to Distributed MIMO scenarios with more than 2 TRPs, while studying beam prediction in both spatial and temporal domains to reduce overhead and improve reliability.
How this was derived
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For the delta summary at the top, the AI compared Kyocera Corporation's consolidated stance at RAN1#124bis
against their stance at RAN1#124 and classified the change as
shifted.
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