Massive MIMO-ISAC Beamforming Design Via Sensing Energy Maximization

In this paper, we investigate the problem of transmit beamforming design for massive multiple-input multiple-output integrated sensing and communications (MIMO-ISAC) systems, through sensing energy maximization. Most of existing methods for transmit beamforming design suffer from high computational complexity in massive MIMO systems, prompting us to develop implementation-friendly designs. Specifically, we employ a structured beamformer composed of the communication precoder and sensing beamformer to simplify the design. The corresponding problem is formulated as maximizing the radar sensing performance in terms of the energy radiated towards the target to ensure sufficient echo from the target, while guaranteeing the signal-to-interference-plus-noise ratio (SINR) for each communication user. In particular, we present two designs with different but affordable complexities based on the instantaneous channel state information (CSI) and statistical CSI, and derive the solutions to them. Numerical examples are carried out to demonstrate the effectiveness of the proposed beamforming designs.