基于能量采集的大规模MIMO系统能效优化

Energy-efficient optimization of massive MIMO systems with energy harvesting

研究基于能量采集的大规模多输入多输出(multiple-input multiple-output,MIMO)系统能效优化问题。保证用户服务质量、能量塔发射功率限制和能量采集时间约束下,为实现上行大规模MIMO系统能效最大化,对能量塔发射功率、能量采集时间进行联合优化。该问题属于非凸优化问题,首先通过分式规划理论将原优化问题等价转换,然后采用块坐标下降(block coordinate descent,BCD)方法,对能量塔发射功率、能量采集时间、系统能效进行迭代求解,提出了一种基于能量采集的大规模MIMO系统的联合优化能效算法(energy-efficient power and time allocation algorithm,EPTA)。仿真结果表明,在保证用户服务质量的情况下,与均时最小QoS保证算法(time-averaged minimum QoS guaranteed algorithm,TA-QoSA)、吞吐量资源分配算法(throughput maximization based power and time algorithm,TPTA)相比,该算法提高了系统能效。

This paper investigated an energy-efficient optimization of massive MIMO systems with energy harvesting.It jointly optimized the power beacon's transmit power and energy harvesting time to maximize the energy efficiency of the uplink massive MIMO systems under the quality of service(QoS),the power beacon's transmit power and energy harvesting time constraints.Because the problem was the non-convex optimization problem,it first transformed to the equivalent optimization problem by fractional programming theory.Then,it proposed an energy-efficient power and time allocation algorithm(EPTA)based on the block coordinate descent(BCD)method to find the power of the power beacon,energy harvesting time and energy efficiency of the system iteratively.Compared with time averaged minimum QoS guaranteed algorithm(TA-QoSA)and throughput maximization based power and time algorithm(TPTA),the simulation results show that the proposed algorithm improves the energy efficiency of the system under the guarantee of user's QoS.