Energy Efficient Hybrid Precoding for Adaptive Partially-Connected mmWave Massive MIMO: A Decomposition-Based Approach

For the prominent superiority in supporting high-data-rate applications with reduced hardware complexity and energy consumption, hybrid precoding in millimeter-wave (mmWave) massive multi-input multi-output (MIMO) system has attracted considerable attentions recently. To adequately utilize the available antenna resources and reduce power consumption, we investigate energy efficient hybrid precoding for an adaptive partially-connected structure in mmWave massive MIMO system with antenna group overlapping to achieve array gain. Specifically, the energy efficient hybrid precoding is firstly formulated as an energy efficiency (EE) maximizing problem, where the number of active phase shifters, the connection relationship between radio frequency chains and antennas, and precoding matrix are jointly optimized. Then, utilizing the diagonal characteristic of digital precoding in a partially-connected structure, we propose a decomposition-based low-complexity approach to tackle the large-scale mix-integer non-convex EE optimization problem in the fully adaptive hybrid precoding scheme. Besides, to provide further insights on how the EE-oriented design affects the system performance, a partially adaptive scheme is also introduced. Finally, simulation results verify the viability and effectiveness of the proposed schemes.