Active Reconfigurable Intelligent Surface Assisted Integrated Sensing, Communications and Computation Energy-Constrained Networks

In this paper, we consider an integrated sensing, communications and computation (ISCC) energy-constrained system, where multiple users with limited energy budgets execute local computing and concurrently offload data to a dual-functional radar communication base station (DFRC-BS), while the DFRC-BS conducts target detection through radar sensing at the same time. We propose an active reconfigurable intelligent surface (ARIS)-assisted ISCC scheme, denoted by ARIS-ISCC, in which the ARIS is employed to facilitate the data offloading from the users to DFRC-BS. To enhance the data collection capability across radar sensing, communication offloading and local computation of the proposed ARIS-ISCC scheme, a weighted total computation bits (WTCB) maximization problem is formulated constrained by the users’ energy limits, power budgets constraints for the DFRC-BS and ARIS, and temporal restrictions. To tackle the high-coupling and non-convexity of the problem, we initially utilize the fractional programming (FP) to reframe the original objective function. Then, we employ the alternating optimization (AO) algorithm to decompose the reformulated problem into distinct sub-problems, which enables us to iteratively optimize one set of variables while keeping others fixed. We derive the closed-form solutions of each sub-problem by developing the Lagrange dual method and linear programming. Numerical results validate the advantages of the proposed ARIS-ISCC scheme compared to the conventional benchmarks regarding to the WTCB.