Study On Suppressing Inter-symbol Interference For Wireless Ultraviolet Scattering Communication

Wireless Ultraviolet Communication(UVC)has the characteristics of all-weather,anti-jamming and secret communication.UVC has significant application value in military and civil fields.Wireless ultraviolet(UV)can realize Non-Line-of-Sight(NLOS)communication by scattering of atmospheric particles,so it doesn't need accurate alignment.However,the scattering of atmospheric particles on UV signal will have obvious multipath effect.The multipath effect will result in serious Inter-symbol Interference(ISI)problems.In order to suppress ISI and improve the performance of NLOS UVC,channel equalization and channel estimation techniques in NLOS UVC are studied in this thesis.Through an improved channel equalization and an optimized channel estimation algorithm,the accurate detection of communication signals and the accurate estimation of channel parameters are realized.The main research contents of this thesis are as follows.(1)According to the model of NLOS UVC channel,the mathematical expression of received signal is established.Fractionally Spaced Equalizer(FSE)is used to equalize the UV signal,and the FSE is implemented blindly with the constant modulus algorithm(CMA).The noise characteristics of received UV signal are studied.The algorithm is improved by the estimation result of signal-to-noise ratio(SNR),which makes the algorithm have better adaptive ability.The simulation results show that the improved CMA-FSE algorithm has good performance in convergence speed and steady-state mean square error(MSE),and the bit error rate(BER)is reduced by 1?2 orders of magnitude compared with the least mean square(LMS)algorithm and the recursive least squares(RLS)algorithm.(2)Based on the Bayesian estimation principle,a Bayesian estimation framework for NLOS UVC channel is established.The joint parameter vectors are used as the state variables to be estimated to realize the synchronous estimation of channel response coefficients and communication signals.This thesis study the method to realize the Bayesian estimation through particle filter(PF)algorithm,but the resampling process in PF is not suitable for the estimation of NLOS UV channel.Therefore,DE-PF channel estimation algorithm is obtained by combining differential evolution algorithm(DEA)to improve particle diversity in PF.The simulation results show that the estimated signal-to-noise ratio of the DE-PF is improved by 5dB?10dB and the BER is reduced by about one order of magnitude compared with the LMS algorithm and the RLS algorithm.In summary,an improved channel equalization and an optimized channel estimation algorithm based on the characteristics of NLOS UVC channel in this thesis can effectively suppress ISI,and improve the performance of communication system when the channel is at the state of severe IS I and small SNR.