Low-Complexity Transmit Beamforming Design for Massive MIMO-ISAC Systems

In this paper, we consider the problem of transmit beamforming design for massive multiple-input multiple-output integrated sensing and communications (MMIMO-ISAC) systems. Different from the existing designs for regular MIMO-ISAC systems, which directly optimize the dual-function beamformer matrix and are computationally expensive especially for large-scale antenna arrays, we propose to construct the beamformer as a weighted sum of the maximum ratio precoder and a desired sensing beamformer. This is motivated by the fact that maximum ratio precoding schemes are simple, and performs well in MMIMO systems. The weights involved in the beamformer are adjusted via optimizing the powers allocated to the users and sensing. A linear programming (LP) problem, which minimizes the total transmit power subject to the performance constraints of communication and sensing, is thus formulated. It is shown that the LP problem can be analytically solved. Therefore, the proposed transmit beamforming design has very low computational complexity. Its effectiveness and performance are illustrated by simulations.