Multi-Objective Optimization-based Transmit Beamforming for Multi-Target and Multi-User MIMO-ISAC Systems
arxiv(2024)
摘要
Integrated sensing and communication (ISAC) is an enabling technology for the
sixth-generation mobile communications, which equips the wireless communication
networks with sensing capabilities. In this paper, we investigate transmit
beamforming design for multiple-input and multiple-output (MIMO)-ISAC systems
in scenarios with multiple radar targets and communication users. A general
form of multi-target 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 reflected signals from different targets, which aligns
with the principles of adaptive MIMO radar. Then, we propose a multi-objective
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 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, simulation results
validate that the proposed method achieves a better tradeoff between multi-user
communication and multi-target sensing performance. Additionally, utilizing the
tight upper bound of sensing MI as a performance metric can enhance the
multi-target resolution capability and angle estimation accuracy.
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