Low-Power Beamforming Design for Near-Field Integrated Sensing and Communication Networks

Integrated sensing and communication (ISAC) has emerged as a cornerstone technology for achieving seamless coverage in next-generation networks. Moreover, the advent of extremely large-scale multiple-input-multiple-output significantly enhances ISAC's potential, facilitating innovative applications in near-field (NF) ISAC. Nonetheless, ISAC networks face numerous challenges, with power consumption being one of the most critical concerns. To address this issue, we propose a novel low-power beamforming approach within the coordinated multipoint (CoMP) ISAC framework. Specifically, our approach involves orchestrating base station (BS) cooperation for seamless coverage and synergistically augmenting the sensing beam with the communication beam to reduce power consumption. By utilizing the NF communication theory, we accurately model signal propagation dynamics and formulate a beamforming optimization problem aimed at minimizing transmit power while adhering to transmission rate and object detection constraints, which is a nonconvex second-order cone programming (SOCP) problem. To overcome the nonconvexity of this problem, we propose a successive convex approximation (SCA)-based beamforming optimization algorithm that ensures convergence. Moreover, we propose a fast-converging algorithm that leverages the unique characteristics of both communication channel and sensing array response vector. Simulation results validate the effectiveness of the proposed scheme for the power minimization problem and yield essential design insights.