NOMA-ISAC via IRS: A Joint Beamforming and Reflecting Optimization Approach

Integrated sensing and communication (ISAC) enables compatible sensing and communications in shared frequency bands. However, the performance of ISAC may be affected by the channel fading and massive connections. Thus, we propose a non-orthogonal multiple access (NOMA) aided ISAC scheme via intelligent reflective surface (IRS) to set up virtual line-of-sight links for multi-user communication and target sensing. Specifically, we aim to maximize the sum rate through the joint optimization of the transmit beamforming at the base station and reflecting at the IRS, while satisfying the sensing requirement. Since the original optimization problem is nonconvex, we decompose it into two subproblems and convert them into convex ones. Then, an alternating optimization algorithm is proposed. Simulation results verify that the proposed scheme can effectively enhance the multi-user NOMA communication performance while ensuring the sensing quality.