Hybrid Beamforming Optimization for Robust Uplink Channel Tracking in Massive MIMO Systems

Hybrid beamforming (HBF) with partially connected antenna structure (PCAS) is crucial for enhancing the capacity and efficiency of massive MIMO with an affordable hardware cost and power consumption. However, the highly compressed measurements pose challenges for channel estimation, emphasizing the need to optimize the HBF for improved channel estimation performance. This letter introduces a novel optimization algorithm for HBF during channel estimation, incorporating the Cramér-Rao bound (CRB) and mutual information (MI) in the objective function to account for both established and emerging propagation paths. Simulations demonstrate that the proposed design significantly enhances channel tracking accuracy compared to various baseline schemes.