Adaptive Multi-Beamforming for Integrated Sensing and Communication System

Multi-beamforming is an effective technique to mitigate interference in the integrated sensing and communication (ISAC) system. This paper proposes an adaptive multi-beamforming approach, in which a demand factor that optimizes the phase weighting factor is developed for synthesizing sensing and communication beams. Based on this demand factor, a novel osprey sparrow optimization (OSO) algorithm is proposed to efficiently calculate the optimal sensing and communication beamforming vectors. Simulation results demonstrate that the proposed approach achieves the desired multi-beamforming, catering to the requirements of sensing and communication. OSO suppresses side lobes with a reduction of 5–10 dB and enjoys more accurate main lobe pointing for linear antenna arrays (LAAs), compared to either sparrow search algorithm (SSA) or particle swarm optimization (PSO). When the size of antenna arrays becomes larger, OSO achieves at least 3-fold convergence speed improvement for planar antenna arrays (PAAs).