In this paper, we consider intelligent reflecting surface (IRS) in a non-orthogonal multiple access (NOMA)-aided Integrated Sensing and Multicast-Unicast Communication (ISMUC) system, where the multicast signal is used for sensing and communications while the unicast signal is used only for communications. Our goal is to depict whether the IRS improves the performance of NOMA-ISMUC system or not under the imperfect/perfect successive interference cancellation (SIC) scenario. Towards this end, we formulate a non-convex problem to maximize the unicast rate while ensuring the minimum target illumination power and multicast rate. To settle this problem, we employ the Dinkelbach method to transform this original problem into an equivalent one, which is then solved via alternating optimization algorithm and semidefinite relaxation (SDR) with Sequential Rank-One Constraint Relaxation (SROCR). Based on this, an iterative algorithm is devised to obtain a near-optimal solution. Computer simulations verify the quick convergence of the devised iterative algorithm, and provide insightful results. Compared to NOMA-ISMUC without IRS, IRS-aided NOMA-ISMUC achieves a higher rate with perfect SIC but keeps the almost same rate in the case of imperfect SIC.

翻译：本文研究了智能反射面（IRS）在非正交多址接入（NOMA）辅助的集成感知与多播-单播通信（ISMUC）系统中的应用，其中多播信号用于感知与通信，而单播信号仅用于通信。我们的目标是探究在非理想/理想连续干扰消除（SIC）场景下，IRS是否提升了NOMA-ISMUC系统的性能。为此，我们构建了一个非凸优化问题，旨在在保证最小目标照射功率和多播速率的同时最大化单播速率。为解决该问题，采用Dinkelbach方法将原始问题转化为等价形式，进而通过交替优化算法及结合顺序秩一约束松弛（SROCR）的半定松弛（SDR）方法进行求解。基于此，设计了一种迭代算法以获得近优解。计算机仿真验证了所提迭代算法的快速收敛性，并提供了富有洞察力的结果。相比无IRS的NOMA-ISMUC系统，IRS辅助的NOMA-ISMUC在理想SIC下可获得更高速率，而在非理想SIC情况下速率几乎保持不变。