R1-2600093 discussion

Beam Management for Multi-TRP transmission in 6GR

From Kyocera Corporation
Status: not treated
WI: FS_6G_Radio
Agenda: 10.5.2.4
Release: Rel-20
Source: 3gpp.org ↗

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.

Position

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.

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