Research On Crosstalk Suppression Of Oam-Mimo Sysyem In Atmospheric Turbulence Channel

Orbital Angular Momentum(OAM)multiplexed communication can increase the channel transmission capacity,but due to the influence of atmospheric channels,the orthogonality between OAM modes could be destroyed during the transmission process,which could caused crosstalk.Like the traditional wireless optical communication,the Multi-Input Multi-Output(MIMO)equalization method can be used to reduce the inter-mode crosstalk and inter-symbol interference of the OAM multiplexed communication system.Aiming at the situation that the traditional blind equalization algorithm applied to OAM multiplexed communication system can not recover multiple signals at the same time,the blind equalization algorithm combined with blind source separation is used to simultaneously suppress multi-channel crosstalk.The main work is as follows:1.This paper introduced the blind equalization algorithm based on cross correlation function(CC)to suppress the crosstalk generated by the OAM multiplexing communication system under atmospheric channel transmission,thereby improving the performance of the communication system.Through numerical simulation,it analyzed the constellation recovery of the output signal,the average bit error rate of the system and the convergence speed of the algorithm under the effect of this algorithm.2.The multiuser kurtosis(MUK)maximization algorithm was a kind of blind source separation algorithm.It can also achieve the function of source separation when it acts on the OAM multiplexing communication system alone,thereby reducing the crosstalk of the communication system.It compared and analyzed its equalization effect with Constant Modulus Algorithm(CMA)through simulation.3.This paper introduced a high-order statistics based blind equalization Algorithm,which combines MUK Algorithm with Modified Constant Equalization Algorithm(MCMA).Then,it mixing efficiency as evaluation indicators.In addition,the experiment uses two response matrices to verify their influence on the closed-loop correction of the system.The experimental research results show that the prediction algorithm can effectively compensate the system delay and improve the convergence speed and depth of the PV,RMS and mixing efficiency in the closed-loop correction.In the case of 1.2km,compared with linear prediction,the number of PV curve convergence iterations in Kalman filter prediction is reduced by about 30 times,but the depth of convergence is basically the same.The convergence depth of the PV curve of the response matrix solved by the state space model is improved by about 0.3?m.When the communication distance is 5km and 10km,the convergence of PV,RMS and mixing efficiency curves fluctuates greatly,but the correction gain exceeds 20%,and the correction effect is greatly improved.