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:我们考虑一种基于速率分裂多路访问(RSMA)的通信与雷达共存(CRC)系统。提出的系统允许基于RSMA的通信系统与多个雷达共享频谱。此外,RSMA通过将消息分为公共部分和私有部分来分别解码干扰并部分将干扰视为噪声,实现了灵活且强大的干扰管理。因此,RSMA基础CRC系统显着提高了通信用户(CUs)的谱效率、能量效率和服务质量(QoS)。然而,RSMA基础CRC系统也带来了新的挑战。由于频谱共享,通信网络和雷达会互相干扰,降低雷达的信干噪比(SINR)以及通信网络CU的数据速率。因此,主要问题是在保证数据传输的QoS要求和多雷达的SINR要求的前提下,最大化CU的总速率。为了实现这些目标,我们制定了一个问题,优化了i)给CU的公共速率分配、公共消息的发射功率和私有消息的发射功率,ii)雷达的发射功率。该问题是具有多个决策参数的非凸问题,难以解决。我们提出两种算法。第一个是顺序二次规划(SQP),可以快速返回局部最优解,并已知为非线性规划方法的最先进技术。第二种是加法逼近方案(AAS),基于将枚举应用于修改后的实例的技术,在合理的时间内全局解决了问题。模拟结果显示,相对于SQP,AAS在总速率方面的提高。