Power Optimization for Integrated Sensing and Communication in Cellular Networks

Integrated sensing and communications (ISAC) is currently a hot research topic and this paper focuses on power allocation problem in multi-cell ISAC in cellular networks. The design of power allocation is formulated as a optimize problem of maximizing communication rate, subject to the constraints of the base stations' (BSs) power budgets and the requirements for sensing signal-to-noise ratio (SNR) at the BSs. Fractional programming (FP) is a mathematical technique that can be used to solve optimization problems where the objective function is a ratio of two functions. By using this approach, we develop an efficient algorithm for solving the power allocation problem in multi-cell ISAC networks. Based on the SNR of BS sensing, we separately examine the cases of using other BS signals to assist sensing and not using other BSs to assist. Simulation results confirm that our proposed algorithm achieves a good balance between performance and computational complexity, and demonstrates that joint sensing by BSs can improve the sum rate.