Toward Energy-Efficient mmWave Cell-Free Massive MIMO Systems: A Hierarchical Hybrid Precoding Framework

In this paper, we investigate energy-efficient hybrid precoding for cell-free massive MIMO (CF-mMIMO) systems at millimeter-wave (mmWave) frequencies. We propose a hierarchical hybrid precoding (HHP) framework to tackle the energy efficiency (EE) optimization problem with two sequential subproblems: fully digital EE optimization and hybrid precoding decomposition. Firstly, by exploiting rate-MMSE equivalence, the central processing unit (CPU) optimizes the fully digital precoder with a Dinkelbach-based weighted minimum mean square error (D-WMMSE) algorithm. Secondly, the access points (APs) perform row-wise parallelized hybrid precoding decomposition via a parallel alternating direction method of multipliers-based alternating minimization (P-ADMM-AltMin) algorithm. Simulation results demonstrate that our proposed HHP framework achieves substantial EE improvements (up to 193.9% higher at most) with computational complexity reduced by a factor proportion to the number of antennas per AP compared with the baselines.