  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 paper, 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 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
cancellation technique. Furthermore, we analyze 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.
