Cooperative Multi-Monostatic Sensing for Object Localization in 6G Networks

Enabling passive sensing of the environment using cellular base stations (BSs) will be one of the disruptive features of the sixth-generation (6G) networks. However, accurate local-ization and positioning of objects are challenging to achieve as multipath significantly degrades the reflected echoes. Existing lo-calization techniques perform well under the assumption of large bandwidth available but perform poorly in bandwidth-limited scenarios. To alleviate this problem, in this work, we introduce a 5G New Radio (NR)-based cooperative multi-monostatic sensing framework for passive target localization that operates in the Frequency Range 1 (FRl) band. We propose a novel fusion-based estimation process that can mitigate the effect of multipath by assigning appropriate weight to the range estimation of each BS. Extensive simulation results using ray-tracing demonstrate the efficacy of the proposed multi-sensing framework in bandwidth-limited scenarios.