Resource Allocation for IRS-Assisted Secure NOMA-ISAC Network

Abstract

In the design of dual-function waveforms for an integrated sensing and communication (ISAC) system, confidential information transmitted by the base station (BS) to legitimate users is designed to be embedded in the radar sensing signal. This generates a critical security concern, as the information becomes vulnerable to eavesdropping by the sensing target, threatening the physical layer security of the system. To address this problem, this paper introduces a non-orthogonal multiple access (NOMA) protocol to mitigate the interference problem in the multiple-input single-output ISAC network. Additionally, the sensing component within the dual-function waveforms is employed not only for target detection but also as artificial noise to interfere with the potential eavesdropper. Furthermore, deploying an intelligent reconfigurable surface (IRS) with optimized phase design in the ISAC network can further enhance the communication security by reshaping the wireless environment. For the IRS-assisted multi-user NOMA-ISAC network, we jointly optimize the resource allocation problem for the precoding matrix of the BS and the phase shift matrix of the IRS, considering constraints including decoding order, quality of service for legitimate users, security, sensing performance, and upper bound on the transmit power, to maximize system throughput. Given the non-convex nature of the optimization problem, an efficient joint optimization algorithm based on semidefinite relaxation and alternating optimization algorithm is proposed to find the solution for the problem. Simulation results validate the convergence of the proposed algorithm and demonstrate its superiority over other benchmark algorithms.