The multi-user multiple-input multiple-output (MU-MIMO) systems can greatly improve the system throughput. An efficient user selection and power allocation schemes are essential to achieve the needed performance. This paper examines energy efficiency maximization under limited feedback in MU-MIMO systems. An expression for the achievable data rate is derived for RRH-user selection which is used to obtain the optimization framework for the energy efficiency (EE). The system EE is optimized through power allocation, RRH-user selection and number of antennas adjustment when the quality of service requirements and maximum transmit power constraints are satisfied. The formulated problem is NP-hard and non-convex. Based on Lagrange dual decomposition and successive convex approximation, a practical scheme is proposed to tackle the problem. It can be observed that there is an improvement of 4% in the energy efficiency of the proposed algorithm as compared with the energy efficiency of the existing algorithm. Furthermore, the computational complexity of the proposed algorithm is discussed. Finally, the proposed algorithm is validated through simulations and the results show that the proposed algorithm outperforms the existing algorithms in terms of the system EE.

多用户多输入多输出（MU-MIMO）系统可以大大提高系统吞吐量。有效的用户选择和功率分配方案对于实现所需的性能至关重要。本文研究了MU-MIMO系统中有限反馈下的能量效率最大化。为RRH用户选择导出了可达到的数据速率的表达式，该表达式用于获得能效（EE）的优化框架。当满足服务质量要求和最大发射功率约束时，可通过功率分配，RRH用户选择和天线数量调整来优化系统EE。提出的问题是NP难的和非凸的。基于拉格朗日对偶分解和逐次凸逼近，提出了解决该问题的实用方案。可以观察到，与现有算法的能量效率相比，该算法的能量效率提高了4％。此外，讨论了所提出算法的计算复杂度。最后，通过仿真验证了该算法的有效性，结果表明该算法在系统EE方面优于现有算法。