R1-2601868 discussion

Discussion on aspects of downlink-based CSI acquisition

From ZTE
Status: not treated
WI: FS_6G_Radio
Agenda: 10.5.3.1
Release: Rel-20
Source: 3gpp.org ↗

Summary

This ZTE document on 6G-R CSI acquisition presents 16 formal proposals and 12 observations covering a broad evolution from 5G-NR. Key areas include a flexible CSI framework with decoupled measurement/reporting, a unified fixed codebook based on enhanced Rel-16 eType-II, downloadable codebooks, AI-powered CSI compression, and early CSI acquisition for initial access and handover scenarios.

Position

ZTE proposes a decoupled CSI acquisition framework where measurement and report configurations, as well as their triggering, are separated to natively support features like AI/ML-based beam management and spatial-domain CSI-RS overhead reduction, and opposes moving CSI containers to L2 signaling, requiring L1 (UCI) to carry CSI reports due to latency, reliability, and overhead concerns. For CSI compression, ZTE proposes a unified fixed codebook based on the Rel-16 eType-II structure with layer-specific SD basis selection when L ≤ 2 and layer-common SD basis selection when L > 2, supplemented by both Type-I-like and Type-II-like downloadable codebooks to cover broader scenarios like multi-panel UEs and near-field. ZTE presents a technical case against prioritizing JSCC/JSCCM for AI-powered CSI compression, arguing that performance gains diminish to ~2.5% SGCS at typical SINR ranges and requiring further justification on NW-side complexity, reliability, PAPR, generality, and scalability, while supporting SSCC with a UE-sided linear matrix and NW-sided AI model. ZTE proposes early CSI acquisition during initial access and inter-cell-cluster handover to enable mTRP CJT for small/medium-sized data packets that dominate >90% of real-field traffic, with early CSI reports transmittable before or after handover command reception. For CSI-RS, ZTE proposes supporting up to 256 ports in a single resource with cross-RB/slot mapping, and a hybrid high-density + low-density CSI-RS transmission pattern with UE-side AI/non-AI channel prediction to reduce overhead for ultra-massive MIMO.

Key proposals

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