Beamforming Design for Integrated Sensing and Communication Systems With Finite Alphabet Input

Joint beamforming for integrated sensing and communication (ISAC) is an efficient way to combine two functionalities in a system at the waveform level. This letter proposes a beamforming design for ISAC systems with finite alphabet signaling. We formulate a problem to maximize the minimum Euclidean distance (MMED) among noise-free received signal vectors under a sensing constraint and a given power constraint. To tackle the formulated optimization problem, we transform it into a semi-definite programming (SDP) and solve it by the semi-definite relaxation (SDR) method. Comprehensive comparisons with existing schemes show that our proposed beamforming offers lower symbol error rate (SER), higher mutual information, and also better sensing performance than existing ISAC beamforming designs.