A Stochastic Optimization Approach to Hybrid Processing in Massive MIMO Systems

The high cost and energy consumption of fully digital massive multiple-input multiple-output (MIMO) systems has led to hybrid designs with fewer radio frequency (RF) chains than antennas. In this letter, we propose an efficient hybrid processing algorithm for point-to-point (P2P) massive MIMO systems that operate in either rich or poor scattering environments. The proposed scheme, i.e., hybrid processing via stochastic approximation with Gaussian smoothing (HPSAGS), alternates between a digital baseband and an analog RF precoder/combiner computation step. The method achieves state-of-the-art performance with low computational cost, which is essential for large MIMO systems.