A VP-AltMin based Hybrid Beamforming in Integrated Sensing and Communication Systems for vehicular networks

Future autonomous vehicles will incorporate high date rate communications and high-accuracy radar sensing capabilities operating in the millimeter-wave (mmWave) and higher frequencies, which results in Integrated sensing and communication (ISAC). Hybrid beamforming (HBF) is an attractive technology for practical vehicular ISAC systems. The HBF with the partially-connected structure (PCS) can effectively reduce the hardware cost and power consumption compared to fully-connected structure (FCS). But the constant-modulus constraint caused by PCS makes the HBF design problem non-convex, which poses a greater challenge. In this paper, we consider the HBF design with PCS as a weighted minimization problem of the communication and radar beamforming errors under the constant-modulus constraints and power constraints. Dual functions of communication and radar are expressed as a trade-off in this question. Despite the optimization problem being non-convex and hard to obtain the global minimizer, we reduce the problem into a two-step subproblem including the analog precoder design and digital precoder design. Then, a variable projection-based alternating minimization algorithm is proposed to solve these problems. Unlike previous works, which focused on the relationship between variables to iteratively solve, our method exploits the intrinsic geometric features of the mmWave channel and the variable projection to simplify the solution of the beamformers. Simulation results demonstrate that the proposed algorithm achieves significantly improved performance in terms of the system spectral efficiency over the existing solutions and greatly reduces the computational complexity.