Cooperative Multi-Monostatic Sensing for Object Localization in 6G Networks
arxiv(2023)
摘要
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 localization and positioning of objects are
challenging to achieve as multipath significantly degrades the reflected echos.
Existing localization 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 (FR1) 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.
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