Sensing Performance Optimization for ISAC with ITS and IRS

In this paper, a novel integrated sensing and communication (ISAC) system architecture is introduced that incorpo rates an intelligent transmission surface (ITS) in the transmitter and an intelligent reflecting surface (IRS) in the transmission channel. The ITS introduces a novel signal modulation architecture for coordinated operation with the base station (BS), while the IRS facilitates efficient signal transmission for the communication users and the sensing target. The main goal is to maximize the beam response gain from the IRS to the sensing target while satisfying the demand of the communication performance for the users. This is realized by collaboratively designing hybrid beamforming strategies at the BS for the simultaneous transmission of communication and sensing signals, along with the ITS and IRS phase shifts. Then, an effective algorithm is proposed that utilizes penalty factors to simplify the optimization problem. Furthermore, an alternating optimization (AO) method is employed to iteratively optimize the relevant variables. Subproblems in this framework are further solved using techniques such as the Lagrange multiplier method, bi section search, the successive convex approximation (SCA), and the alternating direction method of multipliers (ADMM). Finally, simulation results demonstrate that the proposed scheme yields a significant enhancement in beam response gain and energy efficiency compared to benchmark schemes.