Power Allocation of Integrated Sensing and Communication System for the Internet of Vehicles

In terms of enhancing the spectrum-sharing capability of the Internet of vehicles (IoV), the integrated sensing and communication (ISAC) systems of the communication transmission and radar detection in the IoV are discussed. Firstly, the optimal power allocation of communication and radar is considered, respectively, and the joint optimization problem of maximizing the communication rate and the Fisher information (FI) of radar sensing is constructed. Then, an adaptive optimization weight factor is introduced to optimize the power allocation of the ISAC system, to achieve a trade-off performance between sensing and communication in the IoV system. Subsequently, the alternating optimization fractional programming and KKT (AO-FP-KKT) algorithm is proposed based on the coupled characteristics of the problem. This algorithm introduces dual variables to construct the Lagrange function, combines fractional programming architecture, and utilizes KKT conditions to obtain closed-form solutions. In particular, the scope of the dual variable is analyzed in detail and proved strictly. Finally, the numerical simulation results show that the effectiveness of the proposed algorithm and its superior performance compared with the existing state-of-the-art power allocation methods are demonstrated. The proposed algorithm enhances the system spectrum-sharing capability and achieves a trade-off between sensing and communication performance.