R1-2600057
discussion
Discussion on aspects of downlink-based CSI acquisition for 6GR air interface
From FUTUREWEI
Summary
Futurewei presents a comprehensive view on 6G downlink CSI acquisition, proposing 15 specific actions and 5 observations. The document argues for adopting the 5G NR MIMO/RS/CSI framework as a baseline for 6G while evolving it with enhancements for upper midband (UMB), AI/ML integration, CSI-RS/report overhead reduction, and hybrid antenna architecture support.
Position
Futurewei proposes adopting the 5G NR MIMO/RS/CSI framework as the baseline for 6G without fundamental paradigm shifts, focusing evolutionary enhancements on UMB support. They propose studying hybrid antenna architectures for UMB base stations with large antenna element counts (e.g., >512 elements, specifically 2048-element combinations with 32-256 TXRUs at 7/15 GHz) and present technical case for simultaneous multi-beam codebooks that enable fast full CSI acquisition in N/K_s orthogonal beams per OFDM symbol. For CSI-RS overhead reduction, they propose structured port-to-RE mapping exploiting beam-domain channel sparsity and a joint channel estimation algorithm based on IDFT, contrasting with AI/ML-based approaches requiring both UE-sided and NW-sided model evaluation. They propose CSI framework simplification through streamlined CSI-ReportConfig/CSI-ResourceConfig settings and require proper conventional non-AI/ML baselines be identified for all AI/ML evaluations. They propose adopting 5G NR two-sided AI/ML CSI compression and further studying JSCC and downloadable codebook approaches while deferring joint source-channel-modulation coding due to higher ecosystem impact.
Key proposals
- Proposal 1 (Sec 2): Adopt 5G NR MIMO/RS/CSI framework as starting point, study UMB support, general SE/UPT enhancements, and fast FR2 beam acquisition.
- Proposal 2 (Sec 2.3): RAN1 to discuss high-level framework principles enabling AI/ML integration from day-1.
- Proposal 4 (Sec 3): Support enhancements for CSI-RS overhead reduction, CSI report overhead reduction, and interference information acquisition.
- Proposal 5 (Sec 3): Consider CSI framework simplification by streamlining CSI report/resource configurations/settings.
- Proposal 6 (Sec 3): Identify proper conventional non-AI/ML baselines and common assumptions for evaluating AI/ML-based CSI acquisition.
- Proposal 7 (Sec 4.1): Investigate low overhead CSI-RS designs with structured mapping between port and RE in spatial, frequency, and time domains.
- Proposal 8 (Sec 4.2.2): Include AI/ML-based CSI-RS overhead reduction and/or CSI prediction in 6G study, covering both UE-sided and NW-sided models.
- Proposal 9 (Sec 5.1): Adopt 5G NR AI/ML-based CSI compression via two-sided models in 6GR study with further evaluations.
- Proposal 10 (Sec 5.2): Include CSI Compression with JSCC and CSI compression with downloadable codebook(s) in 6G study.
- Proposal 11 (Sec 6.1): Make hybrid antenna architecture with large antenna elements and moderate TXRUs a key focus for UMB base stations.
- Proposal 13 (Sec 6.2): Study full CSI acquisition acceleration for hybrid BS antennas to support efficient MU-MIMO.
- Proposal 14 (Sec 6.3): Study extensions of 5G NR CSI-RS design and Type II codebook framework for fast full CSI acquisition by hybrid BS antennas.
- Proposal 15 (Sec 7): Support advanced interference measurement and reporting, including interference statistics and prospective DL interference probing.