Huawei · 9.1.1

Huawei proposes expanding CSI-RS resource set sizes to up to 256 beams to support AI/ML training and inference, rejecting legacy limits of 64. They require the associated ID for UE-side models to be strictly limited within a single cell to prevent proprietary disclosure and reduce NW management burden. Huawei opposes extending Rel-17 TCI state signaling for BM-Case 2 future time instances, arguing the overhead savings are insignificant compared to the implementation complexity. They define a specific Beam Accuracy Indicator (BAI) metric based on a 'Top-M/K' accuracy state and propose discontinuous CPU occupation rules to handle long observation windows in BM-Case 2. Additionally, they propose separate CPU counting for AI/ML versus legacy CSI reporting and introduce a memory occupancy alignment mechanism to manage UE storage constraints.

Huawei proposes studying mechanisms to support beam sets exceeding 64 resources, either through multiple legacy sets or a single set up to 256 resources. They require the associated ID for UE-side models to be limited to a cell-specific manner to avoid proprietary disclosure and NW burden, and propose applying the ID to a pair of Set A and Set B. Huawei opposes extending Rel-17 TCI state activation for BM-Case 2 future time instances, citing insignificant overhead savings and substantial implementation complexity. They propose reusing existing TCI state timelines for predicted beams and support reporting more than 4 predicted beams (K>4) for UE-side inference. For monitoring, they prefer dedicated CSI report configurations (Option 2) to separate inference and monitoring processes, and propose defining CPU/memory requirements per AI/ML functionality.