Research On The Precoding Algorithm For Massive MIMO System

As the key technology of 5G,massive MIMO(massive multiple-input multiple-outp-ut)technology is based on multiple inputs and multiple outputs.By increasing the number of transmitter antennas,massive MIMO can made full u se of space resources to serve more users,improve the spectral efficie ncy of the system and increase the capacity and throughput of the system.However,the more number of antennas and the number of users the more interference of the system,which mainly includes noise interference,interference between users and inter cell i nterference.In order to suppress these interference,we need to adopt some signal processing techniques.As the limited power consumption and processing capacity of the user terminal,the precoding technology based on the transmitter has become the main interference suppression technology in the downlink.In this paper,based on the classical precoding techniques in traditional MIMO,a precoding algorithm for massive MIMO system is studied.Firstly,The paper introduces the channel capacity and channel characteristics of the traditional MIMO system.When the number of antennas and users increases,the channel characteristics of massive MIMO systems will change,the noise and interferenc e will also become different,and the signal processing methods will also change.Then the principle of precoding and the classical linear precoding algorithms are introduced in detail,including zero forcing precoding,minimum mean square error precoding and precoding based on singular value decomposition.Furthermore,two typical nonlinear precoding algorithms,DPC algorithm and THP algorithm,are introduced.These linear and nonlinear algorithms are simulated and compared.It is found that the rational s ystem capacity can be achieved by using simple linear precoding when the number of antennas at the transmitter is increased to the number of massive antenna arrays.The high complexity of nonlinear precoding limits its application in large-scale MIMO systems.It is concluded that linear precoding with relatively simple complexity is reasonable and feasible in massive MIMO systems.Secondly,the classical block diagonal algorithm is improved in the single cell multi-user scenario in TDD mode and the LO-BD algorithm is proposed.The block diagonal algorithm under low SNR and high symbol error rate of this lack,adding noise impact factor based on block diagonal algorithm.It damages to the low SNR orthogonality between user channel but improves the algorithm's robustness in restraining noise.Considering the power gain brought by massive MIMO system and the actual situation of single terminal antenna,the number of singular value decomposition in BD algorithm is reduced,thus reducing the complexity of BD algo rithm.The simulation results also show that the LO-BD algorithm has more advantages than the traditional BD algorithm in low SNR.Although the complexity of BD algorithm is lower than BD algorithm,it still involves matrix inversion and singular value dec omposition(SVD).In order to adapt to massive MIMO system,it is necessary to reduce the complexity of the algorithm.Finally,in this paper,it proposes a QR decomposition-based QR-BD algorithm,which uses QR decomposition instead of singular value decom position to suppress the interference between users.The simulation results show that the complexity of the proposed QR-BD algorithm is only 1 / K of the BD algorithm even so it has a slightly lower performance.The proposed algorithm is suitable for trans mission requirements of the massive MIMO system.