We consider a rate-splitting multiple access (RSMA)-based communication and radar coexistence (CRC) system. The proposed system allows an RSMA-based communication system to share spectrum with multiple radars. Furthermore, RSMA enables flexible and powerful interference management by splitting messages into common parts and private parts to partially decode interference and partially treat interference as noise. The RSMA-based CRC system thus significantly improves spectral efficiency, energy efficiency and quality of service (QoS) of communication users (CUs). However, the RSMA-based CRC system raises new challenges. Due to the spectrum sharing, the communication network and the radars cause interference to each other, which reduces the signal-to-interference-plus-noise ratio (SINR) of the radars as well as the data rate of the CUs in the communication network. Therefore, a major problem is to maximize the sum rate of the CUs while guaranteeing their QoS requirements of data transmissions and the SINR requirements of multiple radars. To achieve these objectives, we formulate a problem that optimizes i) the common rate allocation to the CUs, transmit power of common messages and transmit power of private messages of the CUs, and ii) transmit power of the radars. The problem is non-convex with multiple decision parameters, which is challenging to be solved. We propose two algorithms. The first sequential quadratic programming (SQP) can quickly return a local optimal solution, and has been known to be the state-of-the-art in nonlinear programming methods. The second is an additive approximation scheme (AAS) which solves the problem globally in a reasonable amount of time, based on the technique of applying exhaustive enumeration to a modified instance. The simulation results show the improvement of the AAS compared with the SQP in terms of sum rate.

翻译：本文研究一种基于速率分割多址（RSMA）的通信与雷达共存系统。该系统中，RSMA通信网络可与多部雷达共享频谱资源。通过将消息拆分为公共部分与私有部分，RSMA能够实现灵活且强大的干扰管理，即对干扰进行部分解码，并将剩余干扰视作噪声处理。基于RSMA的共存系统显著提升了通信用户的频谱效率、能量效率及服务质量。然而，该新系统也带来新挑战：频谱共享导致通信网络与雷达相互干扰，降低了雷达的信干噪比以及通信网络中用户的数据速率。因此，核心问题是在保障通信用户数据传输服务质量要求与多部雷达信干噪比需求的前提下，最大化通信用户的总和速率。为此，我们构建了一个优化问题，同时优化以下参数：i) 通信用户的公共速率分配、公共消息发射功率及私有消息发射功率；ii) 雷达的发射功率。该问题具有非凸特性且包含多个决策变量，求解难度较大。我们提出两种算法：第一种基于序列二次规划（SQP）的算法可快速返回局部最优解，是目前非线性规划方法中的前沿技术；第二种为加性近似方案（AAS），通过对修正实例执行穷举搜索，能在合理时间内求得全局解。仿真结果表明，在总和速率性能方面，AAS优于SQP算法。