A Research On DOA Estimation Algorithm Of Low Complexity Wideband Signal In Massive MIMO System

Massive multiple-input multiple-output(Massive MIMO)technology meets the demanding transmission services of 5G and next-generation mobile communication systems by using a large number of antennas in space.Massive MIMO system can improve communication quality by using a large number of antennas.The premise of ensuring high quality communication is to obtain accurate channel state information(CSI),while the direction of arrival(DOA)technology of array signal can accurately estimate the angle parameter of the user's direction of arrival,and provide accurate CSI for the communication system.Therefore,DOA estimation technology can ensure the performance of massive MIMO system,which has become the focus of many researchers.A variety of communication technologies in modern communication systems adopt wideband signals to increase communication speed and information transmission capacity,and the application of wideband communication system is more extensive.DOA estimation of wideband signals is affected by different signal frequencies,and the traditional narrowband DOA estimation technology is becoming increasingly inapplicable,which brings great challenges to the research of DOA estimation for wideband signals.Incoherent signal subspace method(ISM)and coherent signal subspace method(CSM)are two classical high-resolution subspace algorithms for wideband signal DOA estimation.Although the CSM algorithm has the advantages of high resolution and small estimation error compared to the ISM algorithm,as the number of antennas in massive MIMO system increases,a large number of matrix calculations will reduce the efficiency of DOA estimation.Therefore,in order to solve the problems of large amount of computation and poor timeliness of estimation in the CSM algorithm of traditional wideband signal DOA estimation in massive MIMO system,we have improved the performance of CSM algorithm from two aspects of simplifying array operation and improving angle search efficiency to achieve better wideband signal estimation performance.The research was carried out from the following three points:(1)Firstly,the array covariance matrix is processed by real value processing for purpose of reducing the computational complexity caused by eigenvalue decomposition in subspace class algorithm,and a real value DOA estimation method is proposed,which can reduce the computation of array data redundancy.(2)Secondly,we use genetic algorithm(GA)in intelligent optimization algorithm to optimize the angle search process in the spectral peak search process,which conduct global search for wideband signal DOA estimation to further improve the search efficiency of wideband signal in massive MIMO system.(3)Finally,in order to reduce the impact of multiple parameter settings in GA algorithm and make up for the defect of premature convergence,this paper will continue to innovative use the simple calculation and less parameters of particle swarm optimization algorithm(PSO),which direct uses wideband signal space spectrum function as the fitness function to optimize the peak search,get an efficient search DOA of the wideband signal angle estimation algorithm.Simulation results show that the algorithms proposed in this paper can accurately estimate the wideband signal DOA,improve the search efficiency,and reduce the computational complexity,which make the traditional wideband signal DOA estimation break through the original limitations and have an important research value for the future development of communication.