InterDigital · 9.1.1

InterDigital proposes clarifying data collection configuration signaling before finalizing associated ID working assumptions, supporting dynamically activated sub-configurations. They require that Set A and Set B be configured via two separate CSI-ResourceConfig Ids and support Set A resources with no physical transmission parameters. They argue for a shared CPU counter between legacy and AI/ML CSI reporting to avoid inefficient resource allocation. InterDigital supports overhead reduction mechanisms, specifically reporting beams within an X dB gap of the best beam, and proposes enhanced reporting of up to 64 RSRP values for network-side models. They propose TCI-state based activation for performance monitoring and specific metrics like 'Top-1 in Top-K' or 'margin-based' accuracy. Finally, they support a procedure to dynamically switch the location of AI/ML inference between UE and network based on workload and performance.

InterDigital supports Option 2 for UE-side model applicability identification, arguing that Option 1 requires excessive configuration overhead for candidate CSI report configurations. They prefer Alt 2 for beam configuration, utilizing a single CSI-ResourceConfigId for both Set A and Set B to minimize specification impacts while supporting scenarios with non-transmitted Set A beams. InterDigital proposes supporting QCL parameter estimation for unmeasured beams via neighboring beams, citing performance data showing Doppler shift errors below 10 Hz and RMS delay spread below 15 ns for 90% of the time. They support UE-assisted performance monitoring (Option 2) and dynamic switching of inference location between UE and network to balance computational load and reporting overhead. Additionally, they propose enhanced reporting for network-sided models, including up to 64 RSRP values and pattern-based reporting mechanisms to reduce overhead without sacrificing prediction accuracy.