Baicells · 9.1.2

Baicells supports sample-based measurements as model input, particularly for Case 3b, arguing they provide superior positioning accuracy compared to path-based measurements across various TRP numbers and bandwidths. They propose specific parameter ranges for Nt’ and k and support reusing legacy reference times and IEs, such as 'LoS/NLoS information' and 'Timing Measurement Quality', to minimize specification impact. For training data collection, Baicells suggests exploring gNB-side model training for Case 3a and redesigning procedures for Case 3b to allow LMF to indicate desired SRS configurations. They argue that new measurement requests and responses are beneficial for Case 3b to avoid bandwidth waste and ensure data alignment. Regarding monitoring, they support options that leverage existing mechanisms for Case 1 to achieve minimum specification effort.

Baicells strongly advocates FOR sample-based measurements over path-based measurements, arguing that sample-based provides superior positioning accuracy (1.06-1.62x better performance) and avoids algorithm inconsistencies between vendors. They push FOR phase information support in Case 3b despite overhead concerns, and advocate FOR minimizing specification impact by reusing existing IEs and procedures wherever possible rather than defining new mechanisms.