Energy-efficient optimization algorithm for massive MIMO systems with joint antenna selection and user scheduling

Antenna selection, user scheduling and power allocation play an important role in improving the performance of the massive multiple-input multiple-output (MIMO) system. In this paper, we propose a low-complexity optimization algorithm for joint antenna selection, user scheduling and power allocation based on the energy-efficiency maximization principle for massive MIMO downlink communication system. First, for the antenna selection and user scheduling, we combine the idea of incremental and decremental selection with the objective of maximizing the energy efficiency of the system, and conduct a two-way alternating search for antennas and users; second, for the user power allocation, we use fractional programming theory and Lagrange duality algorithm obtain a closed-form solution for the optimal energy efficiency power, and the three parameters are optimized iteratively to obtain the optimal energy efficiency of the system. The simulation results show that the proposed algorithm can achieve a great performance with low complexity, thus it can effectively reduce the energy consumption in massive MIMO systems.