Networked Integrated Sensing and Communications for 6G Wireless Systems

• Published in: IEEE internet of things journal Vol. 11; no. 17; pp. 29062 - 29075
• Main Authors: Li, Jiapeng, Shao, Xiaodan, Chen, Feng, Wan, Shaohua, Liu, Chang, Wei, Zhiqiang, Wing Kwan Ng, Derrick
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.09.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 6G mobile communication; Algorithms; Array signal processing; Beamforming; Beamforming design; Collaboration; Communication; Communications systems; computational imaging; Computational modeling; Error analysis; Imaging; Integrated sensing and communication; integrated sensing and communication (ISAC); networked sensing; Nodes; Sensors; sixth generation (6G); Wireless communications; Wireless sensor networks
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2024.3406598

Integrated sensing and communication (ISAC) is envisioned as a key pillar for enabling the upcoming sixth generation (6G) communication systems, requiring not only reliable communication functionalities but also highly accurate environmental sensing capabilities. In this article, we design a novel networked ISAC framework to explore the collaboration among multiple users for environmental sensing. Specifically, multiple users can serve as powerful sensors, capturing back scattered signals from a target at various angles to facilitate reliable computational imaging. Centralized sensing approaches are extremely sensitive to the capability of the leader node because it requires the leader node to process the signals sent by all the users. To this end, we propose a two-step distributed cooperative sensing algorithm that allows low-dimensional intermediate estimate exchange among the neighboring users, thus eliminating the reliance on the centralized leader node and improving the robustness of sensing. This way, multiple users can cooperatively sense a target by exploiting the block-wise environment sparsity and the interference cancelation technique. Furthermore, we analyse the mean-square error of the proposed distributed algorithm as a networked sensing performance metric and propose a beamforming design for the proposed network ISAC scheme to maximize the networked sensing accuracy and communication performance subject to a transmit power constraint. Simulation results validate the effectiveness of the proposed algorithm compared with the state-of-the-art algorithms.