Joint Resource Allocation and User Association for Multi-Cell Integrated Sensing and Communication Systems

Abstract The densification of the orthogonal frequency division multiplexing (OFDM) based fifth-generation (5G) communication systems, as well as integrating sensing and communication functionalities, have promoted the development of integrated-sensing-and-communication (ISAC) dense cellular networks (DCNs). In the OFDM-based ISAC-DCN, multiple base stations simultaneously serve mobile users and sense targets based on the echo of downlink (DL) communication signals. In this paper, focusing on the interference management of the ISAC-DCN, we investigate the multi-dimension resource allocation problem. In particular, we aim at maximizing the network utility by jointly optimizing sub-band allocation, user association, and transmission power under the sensing signal-to-interference-plus-noise ratio (SINR) constraint. The problem is decomposed into three sub-problems. Subsequently, we propose a greedy genetic algorithm (GRGA) to solve the sub-band allocation sub-problem, and the Hungarian algorithm and successive convex approximation (SCA) technique are employed to execute user association and transmission power control, respectively. Simulation results show that the proposed algorithm significantly improves the network utility, achieves higher detection probability and illustrates the trade-off between sensing and communication performances.