Near-Field Integrated Sensing and Communication in Cognitive Radio Networks

This article introduces a novel concept of near-field integrated sensing and communication (ISAC) within a cognitive radio (CR) framework. The secondary ISAC transmitter, equipped with an extremely large-scale array, aims to minimize transmit power while meeting the requirements for both communication and sensing, as well as satisfying an interference constraint for the primary receiver. We initially solve the formulated nonconvex problem using a semidefinite relaxation approach to achieve a globally optimal solution. To reduce computational complexity, we propose two suboptimal beamforming strategies: 1) zero-forcing (ZF)-based and 2) maximum ratio transmission (MRT)-based beamforming designs. These approaches provide a practical tradeoff between performance and complexity by fixing beam directions according to the principles of ZF and MRT. Additionally, we develop a robust beamforming design under imperfect channel state information in the communication and interference channels, ensuring reliable performance across all possible channel realizations within the uncertainty bounds. Simulation results confirm the effectiveness of the proposed methods, demonstrating power-efficient joint communication and sensing capabilities within the CR scenario.