ISAC Beamforming Design Based on a Matrix Nearness Formulation With Improved Efficiency

We propose an integrated sensing and communication (ISAC) beamforming method that performs joint multiple input multiple-output (MIMO) radar sensing and multi-user MIMO communication. Our approach builds on a matrix nearness formulation of the MIMO radar problem and utilizes our recently proposed efficient solver, where the computational complexity is dominated by an eigenvalue decomposition (EVD) evaluation at each iteration. We extend this formulation to an ISAC scenario by incorporating minimum signal-to-noise ratio constraints as communication design criteria, only requiring statistical channel state information knowledge at base station. Furthermore, we propose a method to avoid the burdensome EVD evaluations in certain iterations, reducing the computation time by up to six times in a massive MIMO setting.