Research On The Signal Detection Algorithm Of Massive MIMO System

With the rapid development of the internet,more and more intelligent terminal,the existing communication system will not be sufficient to support the needs of mobile communications data in the next few years,which greatly stimulated the research of the next generation of communications.Massive Multiple-input Multiple-output(Massive MIMO)is considered to be one of the key technologies of 5G,compared to the traditional MIMO technology,which can greatly improve the spectrum efficiency and energy efficiency,through increasing the number of antennas at the base station side.However,with the increasing number of antennas,the performance and complexity of the traditional detection algorithms are difficult to meet the needs of the next generation communication system.Based on this case,this paper theoretically analyzes the system model of massive MIMO.When the the number of base station antennas is far larger than the number of users in massive MIMO system,the diagonal elements of the channel are dominated,.according to the minimum mean square error(MMSE)algorithm three iteration algorithms are introduced to replace the matrix inverse operation directly.Through its complexity and performance analysis,simulation results show that this method can meet the communication needs of the future.For the nonlinear detection algorithm,two kinds of artificial intelligence search algorithm are introducted,namely the Likelihood Ascent Search algorithm(LAS)and Reactive Tabu Search algorithm(RTS).We analyzes the principle and the corresponding algorithm complexity,and has made the corresponding improved algorithm.In different parameters setting of massive MIMO,simulation results show that these two algorithms have massive MIMO systems characteristics,but when high order modulation is used,the performance can not meet the demand.Finally,we put forward another algorithm,the approximate message passing algorithm,which is based on maximum a posteriori estimation(MAP).Through the factor graph model,we deduced the principle of AMP algorithm,analysis the complexity of AMP algorithm and compare it to MMSE algorithm.In different parameters setting,simulation results show that this algorithm can reach the performance and MMSE through lower number of iteration,which also solve the problem of high order QAM modulation.