Kullback-Leibler Divergence Based ISAC Constellation and Beamforming Design in the Presence of Clutter

Integrated sensing and communication (ISAC) is regarded as a pivotal technology for 6G communication. In this paper, we employ Kullback-Leibler divergence (KLD) as the unified performance metric for ISAC systems and investigate constellation and beamforming design in the presence of clutters. In particular, the constellation design problem is solved via the successive convex approximation (SCA) technique, and the optimal beamforming in terms of sensing KLD is proven to be equivalent to maximizing the signal-to-interference-plus-noise ratio (SINR) of echo signals. Numerical results demonstrate the tradeoff between sensing and communication performance under different parameter setups. Additionally, the beampattern generated by the proposed algorithm achieves significant clutter suppression and higher SINR of echo signals compared with the conventional scheme.