Research On Sparse Channel Equalization Algorithm In Underwater Acoustic Communication

As the country attaches great importance to the development strategy of the marine economy,the related underwater acoustic communication,as an effective means of marine environment monitoring and acquisition of marine information,is gradually becoming the focus of research in the field of communication.However,the underwater acoustic channel environment is complex,serious multipath effect,abundant environmental noise,serious doppler frequency shift,etc.all bring huge challenges to underwater acoustic communication.The channel equalization technology,as the most effective means to combat the multipath effect,plays a vital role in the reliability and stability of the entire communication system.The underwater acoustic channel has natural sparsity,so the prior information of channel sparsity can be fully utilized to speed up the convergence speed of the channel equalization algorithm.Due to the relative motion of the communication transceiver and the fluctuation of seawater,a time-varying phase offset will be superimposed on the received signal.When the channel equalizer processes signals with jittered phase noise,the tap value of the equalizer may be deflected.As a result,the performance of the equalizer plummets.The equalizer combined with the phase-locked loop can track the time-varying phase noise in real time and improve the reliability of the underwater acoustic communication system.Based on the above background,the main contributions of this thesis are as follows:Firstly,this thesis introduces the development history and research status of underwater acoustic communication technology.Then the channel equalization technology is summarized,and the advantages and disadvantages of various adaptive equalization methods are introduced.Secondly,inspired by the Zero Attracting Least Mean Square（ZA-LMS）algorithm,this thesis proposes an equalization called Zero Attracting Sparse Control Proportional Minimum Symbol Error Rate（ZA-SC-PMSER）equalization algorithm,which forces small amplitude equalizer taps to be drawn towards zero during iterations by adding a sparse constraint that approximates the ₀l norm to the objective function.The iterative formulas of the algorithm under linear equalizer and decision feedback equalizer are deduced respectively.Simulations are carried out under the conditions of sparse simulated channels and actual collected static underwater acoustic channels,and the effectiveness of the ZA-SC-PMSER algorithm is verified.Finally,for the traditional equalizer combined with the phase-locked loop,the update of the phase-locked loop parameters is based on the minimum mean squared error（Minimum Mean Squared Error,MMSE）criterion.When the mean square error of the system is the smallest,the symbol error rate is not necessarily the smallest.Aiming at this problem,this thesis proposes a phase-locked loop phase tracking method based on the Minimum Symbol Error Rate（MSER）criterion.Simulation experiments are carried out under sparse analog channels with dithered phase noise and real time-varying underwater acoustic channels.The results show that the proposed algorithm has lower symbol error rate and faster convergence.