The collaborative sensing of multiple Integrated sensing and communication (ISAC) base stations is one of the important technologies to achieve intelligent transportation. Interference elimination between ISAC base stations is the prerequisite for realizing collaborative sensing. In this paper, we focus on the mutual interference elimination problem in collaborative sensing of multiple ISAC base stations that can communicate and radar sense simultaneously by transmitting ISAC signals. We establish a mutual interference model of multiple ISAC base stations, which consists of communication and radar sensing related interference. Moreover, we propose a joint optimization algorithm (JOA) to solve the collaborative precoding problem with total power constraint (TPC) and perantenna power constraint (PPC). The optimal precoding design can be obtained by using JOA to set appropriate tradeoff coefficient between sensing and communication performance. The proposed collaborative precoding design algorithm is evaluated by considering sensing and communication performance via numerical results. The complexity of JOA for collaborative precoding under TPC and PPC is also compared and simulated in this paper.
翻译:综合遥感和通信多台基站的协作感测是实现智能运输的重要技术之一; 消除ISAC基站之间的干扰是实现协作感测的先决条件; 在本文件中,我们侧重于通过传输ISAC信号同时进行通信和雷达感知的多台ISAC基站的合作感测中消除相互干扰的问题; 我们建立了多台ISAC基站的相互干扰模式,其中包括通信和雷达感测干扰; 此外,我们提议采用联合优化算法(JOA)解决合作预编码问题,同时使用总功率限制(TPC)和永久电能限制(PPC)解决协作预编码问题; 最佳的预编码设计可以通过使用JAA在感测和通信性能之间设定适当的权衡系数来获得; 拟议的合作预编码算法是通过数字结果考虑遥感和通信表现来评估的; 本文还比较和模拟了根据TPC和PPC进行协作预编码的JOA的复杂性。