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Environment Sensing Considering the Occlusion Effect: A Multi-View Approach

Tong, X; Zhang, Z; Zhang, Y; Yang, Z; Huang, C; Wong, KK; Debbah, M; (2022) Environment Sensing Considering the Occlusion Effect: A Multi-View Approach. IEEE Transactions on Signal Processing , 70 pp. 3598-3615. 10.1109/TSP.2022.3185892. Green open access

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Abstract

In this paper, we consider the problem of sensing the environment within a wireless cellular framework. Specifically, multiple user equipments (UEs) send sounding signals to one or multiple base stations (BSs) and then a centralized processor retrieves the environmental information from all the channel information obtained at the BS(s). Taking into account the occlusion effect that is common in the wireless context, we make full use of the different views of the environment from different users and/or BS(s), and propose an effective sensing algorithm called GAMP-MVSVR (generalized-approximate-message-passing-based multi-view sparse vector reconstruction). In the proposed algorithm, a multi-layer factor graph is constructed to iteratively estimate the scattering coefficients of the cloud points and their occlusion relationship. In each iteration, the occlusion relationship between the cloud points of the sparse environment is recalculated according to a simple occlusion detection rule, and in turn, used to estimate the scattering coefficients of the cloud points. Our proposed algorithm can achieve improved sensing performance with multi-BS collaboration in addition to the multi-views from the UEs. The simulation results verify its convergence and effectiveness.

Type: Article
Title: Environment Sensing Considering the Occlusion Effect: A Multi-View Approach
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TSP.2022.3185892
Publisher version: https://doi.org/10.1109/TSP.2022.3185892
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Environment sensing, integrated sensing and communication (ISAC), multi-view sensing, occlusion effect
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10153071
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