Multiobjective-Optimization-Based Transmit Beamforming for Multitarget and Multiuser MIMO-ISAC Systems
Chunwei Meng, Zhiqing Wei, Dingyou Ma, Wanli Ni, Liyan Su, Zhiyong Feng
Abstract
Integrated sensing and communication integrated sensing and communications (ISAC) is an enabling technology for the sixth-generation mobile communications, which equips the wireless communication networks with sensing capabilities. In this article, we investigate transmit beamforming design for the multiple-input and multiple-output (MIMO)-ISAC systems in scenarios with multiple radar targets and communication users. A general form of multitarget sensing mutual information (MI) is derived, along with its upper bound, which can be interpreted as the sum of individual single-target sensing MI. Additionally, this upper bound can be achieved by suppressing the cross-correlation among the reflected signals from different targets, which aligns with the principles of adaptive MIMO radar. Then, we propose a multiobjective optimization framework based on the signal-to-interference-plus-noise ratio of each user and the tight upper bound of sensing MI, introducing the Pareto boundary to characterize the achievable communication-sensing performance boundary of the proposed ISAC system. To achieve the Pareto boundary, the max-min system utility function method is employed, while considering the fairness between the communication users and radar targets. Subsequently, the bisection search method is employed to find a specific Pareto optimal solution by solving a series of convex feasible problems. Finally, the simulation results validate that the proposed method achieves a better tradeoff between the multiuser communication and multitarget sensing performance. Additionally, utilizing the tight upper bound of sensing MI as a performance metric can enhance the multitarget resolution capability and angle estimation accuracy.