| Massive MIMO technology is one of the key technologies of 5G.The number of antenna arrays on the base station side can reach hundreds,which can significantly improve channel capacity and spectrum efficiency.In the deployment,the number of radio links increases with antennas increasing,and the user-side preprocessing in the downlink increases the difficulty,which affects its application in practice.Therefore,this paper systematically studies antenna selection techniques and precoding techniques in Massive MIMO systems.The antenna selection technology can effectively reduce the cost of the radio link and reduce the computational complexity.The precoding technology can eliminate the interference between multiple antennas and reduce the processing complexity of the user end.The main research contents and results of this paper are as follows:(1)The channel capacity characteristics and channel fading model of Massive MIMO system are analyzed.Several classical antenna selection algorithms are discussed.The simulation analysis shows that the norm based selection(NBS)has less computational complexity,and based on maximizing system sum capacity algorithm can get a large system capacity.And an improved antenna selection algorithm is proposed.The proposed algorithm first selects a part of the antenna according to the norm-based antenna selection criterion,which can reduce the computational complexity,and then select the number of target antennas from the selected number of partial antennas.The process takes maximum capacity as the goal function.The object function is transformed into a convex problem and solved by convex optimization,which can obtain a large system capacity.The simulation results show that the system capacity of the improved algorithm is increased by 2.75bps/Hz compared with the NBS algorithm when the signal-to-noise ratio(SNR)is 18dB,the number of base station antennas(M)is 128,and the number of selected antennas(N)is 3.Compared with the maximizing system sum capacity algorithm,its complexity decreases from O(M3 5)to 0((2N)3 S).(2)The precoding algorithm in traditional MIMO system is studied.The advantages and disadvantages of based on zero-forcing,mean square error,signal-to-leakage-plus-noise ratio and signal-to-interference-noise ratio precoding are analyzed.The research results show that the performance of the signal leakage ratio precoding is not as good as the other three methods,but the solution of the precoding matrix is only related to its own precoding vector and independent of other users,which is more suitable for the Massive MIMO system.Based on this,a joint antenna selection precoding algorithm is proposed.The idea is to use the channel matrix selected by the antenna to solve the SLNR-based precoding matrix.The system performance and complexity of the proposed joint algorithm is analyzed with simulations.The simulation results show that the joint precoding algorithm has better bit error rate compared with the existing precoding algorithms at low SNR.The system capacity gain is about 1.8 bps/Hz,and the complexity is reduced by about(M2-N2)when the high signal-to-noise ratio(SNR)is 20dB,the number of base station antennas(M)is 256,and the number of selected antennas(N)is 3. |
