Abstract
In this paper, we investigate a novel integrated communications, computing, and sensing (ICCS) network, where a multi-functional base station (BS) performs downlink communication , target sensing and edge computing. To examine the overall performance of the system under consideration, a weighted sum rate (WSR) maximization problem is formulated by jointly optimizing information beamforming, sensing covariance matrix, sensing echo receiving beamforming, offloading signal receiving beamforming, local computing resources, edge computing resources and offloading strategy. The formulated problem consists of multiple coupled variables, which leads to its non-convexity. To circumvent this issue, we propose an efficient alternating iterative optimization algorithm, which decomposes the original problem into four subproblems to be solved alternately. Specifically, we develop an effective algorithm based on the quadratic transform fractional programming approach to optimize the information beamforming, sensing covariance matrix, sensing echo receiving beamforming and edge computing resources. Then, the La-grangian dual method is used to optimize the offloading signal receiving beamforming. We derive a closed-form solution for the local computing resource. Meanwhile, a coordinate descent (CD) method is proposed to obtain the offloading strategy. The final solutions are obtained by alternatively optimizing the above subproblems until convergence. Finally, numerical results are presented to show the efficiency of the proposed algorithm in comparison to the existing benchmark schemes. Index Terms—Integrated sensing and communication, computing , weighted sum rate.