Integrated sensing and communication (ISAC) has been recognized as one of the key technologies for future wireless networks, which potentially need to operate in multiple frequency bands to satisfy ever-increasing demands for both communication and sensing services. Motivated by this, we consider the sum sensing rate (SR) optimization for a cooperative ISAC system with linear precoding, where each base station (BS) works in a different frequency band. With this aim, we propose an optimization algorithm based on the semi-definite rank relaxation that introduces covariance matrices as optimization variables, and we apply the inner approximation (IA) method to deal with the nonconvexity of the resulting problem. Simulation results show that the proposed algorithm increases the SR by approximately 25 % and 40 % compared to the case of equal power distribution in a cooperative ISAC system with two and three BSs, respectively. Additionally, the algorithm converges in only a few iterations, while its most optimal implementation scenario is in the low power regime.

翻译：集成感知与通信（ISAC）已被认为是未来无线网络的关键技术之一，未来网络可能需要在多个频段运行，以满足日益增长的通信与感知服务需求。受此启发，我们研究了采用线性预编码的协作式ISAC系统的总感知速率优化问题，其中每个基站在不同频段工作。为此，我们提出了一种基于半定秩松弛的优化算法，该算法引入协方差矩阵作为优化变量，并采用内逼近方法处理由此产生的非凸问题。仿真结果表明，在配备两个和三个基站的协作式ISAC系统中，与等功率分配方案相比，所提算法分别将感知速率提升了约25%和40%。此外，该算法仅需数次迭代即可收敛，其最优实施场景为低功率工作状态。