Integrated Sensing, Communication and Computing Through Joint Beamforming and D2D–MEC Cooperative Offloading

Abstract

This paper investigates an integrated sensing, communication, and computing network enabled by joint beamforming and cooperative device-to-device (D2D) and mobile edge computing (MEC) offloading. In the considered system, multiple full-duplex integrated sensing and communication devices perform target sensing while offloading partial latency-sensitive computation tasks through D2D and MEC links, thereby exploiting the complementary advantages of short-range D2D communication and the abundant computing resources of the MEC server. A D2D and MEC co-offloading framework is developed that simultaneously optimizes transceiver beamforming, task assignment, and computation resource allocation, with the aim of minimizing overall computation latency while ensuring sensing performance. To address the intractable issue of the formulated optimization problem, closed-form solutions of receive beamformers are first derived by solving minimum variance distortionless response problems. Subsequently, an alternating optimization algorithm is employed to decouple the original problem into two subproblems. To address their non-convexity, we apply semi-definite relaxation and successive convex approximation to transform each subproblem into a convex form and integrate penalty terms into the objective functions to promote rank-one solutions. Numerical results demonstrate that, compared to the state-of-the-art schemes, the proposed scheme achieves significant latency reduction under limited power and computing resources, while maintaining a high sensing signal-to-interference-plus-noise ratio.