Robust Resource Optimization for IRS-Assisted ICCS Systems With Imperfect CSI

In this article, we study the robust resource optimization for the intelligent reflecting surface (IRS)-assisted full-duplex (FD) integrated communication, computing, and sensing (ICCS) systems. The base station (BS) serves uplink computing users, downlink communication users, and sense targets simultaneously, while the imperfect channel state information (CSI) from IRS to users is considered. Next, we formulate an optimization problem of maximizing sum rate by jointly designing the BS transmit/receive beamforming, IRS reflection coefficients, computing user transmit power and local computing resources. Due to its difficulty to directly solve the formulated problem, we divide it into several subproblems and propose an alternative iterative optimization algorithm. Then, by applying the S-Procedure, singular value decomposition (SVD), and successive convex approximation techniques, each subproblem is transformed into the semidefinite programming (SDP), and the semidefinite relaxation (SDR) is applied to obtain the solution by dropping the rank-one constraint. The final solutions are obtained by alternatively solving all subproblems until convergence. Finally, the simulation results show the performance of the proposed scheme outperforms that of baseline schemes.