Integrated sensing and communications (ISAC) is envisioned as a key technology for future wireless communications. In this paper, we consider a downlink monostatic ISAC system wherein the base station serves multiple communications users and sensing targets at the same time in the presence of clutter. We aim at both guaranteeing fairness among the communications users while simultaneously balancing the performances of communications and sensing functionalities. Therefore, we optimize the transmit and receive beamformers to maximize the weighted minimum signal-to-interference and clutter-plus-noise ratios. The design problem is highly challenging due to the non-smooth and non-convex objective function and strongly coupled variables. We propose two efficient methods to solve the problem. First, we rely on fractional programming and transform the original problem into convex sub-problems, which can be solved with standard convex optimization tools. To further reduce the complexity and dependence on numerical tools, we develop a novel approach to address the inherent non-smoothness of the formulated problem. Finally, the efficiencies of the proposed designs are demonstrated by numerical results.

翻译：集成感知与通信（ISAC）被视作未来无线通信的关键技术。本文研究一种下行单站ISAC系统，其中基站在杂波存在的情况下同时服务多个通信用户与感知目标。我们的目标是在保障通信用户间公平性的同时，平衡通信与感知功能的性能表现。为此，我们通过优化发射与接收波束成形器，以最大化加权最小信号与干扰加杂波噪声比。由于目标函数的非光滑与非凸特性以及变量间的强耦合性，该设计问题极具挑战性。我们提出了两种高效求解方法。首先，基于分式规划理论将原问题转化为凸子问题，这些子问题可利用标准凸优化工具求解。为进一步降低复杂度并减少对数值工具的依赖，我们提出了一种新方法来处理所构建问题固有的非光滑性。最后，通过数值结果验证了所提设计方案的有效性。