ZTE · 9.1.4.1

ZTE proposes conducting comparisons between Case 2 and Case 3 for potential down selection to reduce specification impact analysis efforts, and deferring specification impact analysis for inter-vendor training collaboration until feasibility studies conclude. For Direction A, ZTE proposes sharing performance targets and model backbone information (if proprietary concerns are maintained) from NW to UE, and resolving data distribution mismatch via associated ID indications or NW-side timely data collection. For Direction B, ZTE argues that training multiple UE-specific encoders is infeasible due to proprietary risks, favoring universal encoders despite potential performance sacrifices, and proposes using associated IDs and continuous monitoring to address data distribution mismatch. For Direction C, ZTE supports using synthetic data from 3GPP statistical channel models as a starting point, with model retraining on real-world data to bridge distribution gaps. Regarding remaining issues, ZTE proposes studying Enhanced Rel-16 eTypeII codebook designs for high-resolution CSI, prioritizing NW-side monitoring based on target CSI with realistic channel estimation, and deprioritizing UE-side monitoring in Rel-19.

ZTE advocates for prioritizing Option 3 (standardized reference model structure + parameter exchange) with NW-first training and over-the-air delivery as the most feasible inter-vendor collaboration approach. They push against Option 4 due to huge dataset exchange overhead and UE-side monitoring due to complexity concerns. ZTE strongly supports down-selecting between Case 2 and Case 3 to reduce specification efforts and favors enhanced Rel-16 eTypeII codebook for data collection over more complex alternatives.