Energy Efficiency Resource Allocation In Massive MIMO Systems

With the explosive growth in the number and type of intelligent terminals,people put forward requirements for the higher demands of data services and performance of mobile communication systems.As one of the key technologies of 5G,Massive MIMO systems are deployed with a large scale antenna array in the base station to provide services for more users.It offers higher transmission speed and lower latency.In order to reduce energy consumption and enhance system performance,the energy efficiency oriented green communication technology has aroused widely attention.Therefore,it is significant to improve the energy efficiency by implementing reasonable resource management in Massive MIMO systems.The system model is formulated to maximize the energy efficiency.And then,an antenna selection strategy on alternating search is proposed to tackle antenna selection problem.Based on the correlation antenna selection,the strategy is combined with incremental and decrement algorithm to search alternately,so as to maximize the energy efficiency.Simulation results indicate that the proposed strategy increases the system energy efficiency with a lower computational complexity.The energy efficiency resource allocation model for the subcarrier frequency block,power and the optimal antenna number of the base station is formulated.It is a non-convex optimization problem,which is divided into two sub problems.Firstly,an improved bat algorithm based on the simulated annealing is proposed to allocate the subcarrier frequency block.And then,the fractional programming is used to allocate the power and the number of antennas.Simulation results show that the proposed algorithm achieves higher energy efficiency and better system performance.