Research On Antenna Selection Algorithms For Massive MIMO System

With the continuous development of the big data information era,people have higher requirements for the rate and quality of information acquisition and transmission.The traditional Multiple-Input Multiple-Output(MIMO)systems are very struggling to meet the demands,the massive MIMO systems can fully exploit space resources,provide more multiplexing gain without consuming additional spectrum resources and improve system performance by deploying a large number of antennas.In the actual communication system,the massive MIMO systems with a large number of antennas can significantly increase the cost and complexity of the system hardware,also limit the antenna performance if radio frequency(RF)links configured for the antennas in the traditional way.Antenna selection technology can decline the actual number of RF links,reduce system costs and losses,ensure the massive MIMO systems' performance at the same time.In this paper,the antenna selection algorithms in massive MIMO systems are mainly discussed and studied.The main research contents are as follows:1)To solve the problem of high computational complexity of antenna selection algorithms in massive MIMO systems,the maximum frobenius norm bidirectional antenna selection algorithm is proposed to improve and optimize the channel capacity after analyzing the characteristics and applicable conditions of different antenna selection algorithms.The algorithm completes antenna selection by using the matrix norm in both increasing empty-set and decreasing full-set directions.The simulation results show that the maximum frobenius norm bidirectional antenna selection algorithm can reduce the computational complexity,adapt to the environment of different numbers of selected antenna,and ensure the system performance.2)To solve the problem that the antennas are easily correlated and the matrix dimension is too high when there are a large number of antennas,the Maxvol partition(Maxvol-P)algorithm is proposed based on the idea of group processing channel matrix.In order to further optimize the system performance,a new transceiver association algorithm which referred to as the new partitioning algorithm is proposed by combining the maximum frobenius norm bidirectional antenna selection algorithm,this algorithm completes antenna selection by processing the partitioned channel sub-matrix.The simulation results show that the new transceiver joint partition antenna selection algorithm can effectively reduce the influence of antenna correlation on the system,adapt to different SNR environments,also have high channel capacity in the environment with low SNR.3)To solve the problem caused by the complex propagation environment of the massive MIMO systems,algorithms are selected dynamically by the thresholds,and a new transceiver joint algorithm which is combined with the maximum frobenius norm bidirectional antenna selection algorithm is proposed which can be referred to as the new threshold algorithm.By analyzing algorithms performance in different communication environment,the algorithm dynamically selects the suitable algorithms for antenna selection according to the relationship between the communication channel parameters and the thresholds.Simulation and derivation demonstrate that the new transceiver joint threshold antenna selection algorithm can adapt to different antenna correlation and SNR environments,and maintain the stability of system performance in the complex propagation environment.