Robust Beamforming for ISAC Systems in Highly Dynamic Scenarios

Location-based beamforming has emerged as a promising approach for both complexity reduction and beam alignment. However, most existing solutions only perform well when the position information is accurate, which is challenging in highly dynamic scenarios with frequent location changes. This paper introduces a novel three-phase location-based beamforming framework that is designed to exhibit robustness against potential position uncertainty. The framework employs Bayesian filtering to tackle the non-Gaussian process in the location prediction phase. A robust optimization problem is then formulated to generate a cubic-like beam, ensuring the quality of service even at the beam edge. Simulation results validate the robustness of our beamforming scheme, demonstrating its ability to maintain stable links and deliver satisfactory channel rate.