Self-Interference-Alleviated Beamforming Towards 6G Integrated Sensing and Communication

We focus on self-interference (SI) alleviated beamforming of 6 G full-duplex integrated sensing and communication (ISAC) systems, for achieving an on-demand sensing and communication performance tradeoff with suppressed SI for diverse user devices. However, SI-alleviated ISAC beamforming is of great challenge due to its complex problem structures and nonconvex optimization problem nature. In order to address this challenge, we propose to use the dual transformation framework for problem simplification, and exploit structured components of the problem model, such as convexity, linearity and fraction, for yielding an efficient iterative optimization solution. The proposed SI-alleviated beamforming method can gracefully take care of communication and sensing requirements with suppressed SI for diverse user devices, thus paving the way for an on-demand ISAC service. It is corroborated by numerical simulations that the proposed SI-alleviated beamforming method outperforms state-of-the-art ISAC beamforming baselines, due to our specially-tailored problem modeling and problem-specific algorithm design.