Research On Channel Estimation And Interference Cancellation Based On Underwater Acoustic OFDM Communication System

The marine environment contains rich resources.With the increasing scarcity of land resources,countries begin to fully exploit and utilize marine resources.In order to ensure safe,reliable and effective resource exploration and development,a reliable underwater communication system needs to be established.Compared with radio and light waves,sound waves become the preferred method for underwater communication systems due to the advantages of the low attenuation and long transmission distance in the underwater circumstance.However,because of the bandwidth constraints,severe fading,noises and multipath effect and other factors,the underwater acoustic channel has become one of the most complex wireless channels.The main content of this thesis is the research of channel estimation and interference cancellation in high-speed underwater acoustic(UA)orthogonal frequency-division multiplexing(OFDM)communication systems.There are many factors that affect the reliability of underwater communication systems.This paper focuses on the influence of strong interference,that is impulsive noise,in the underwater.Although the use of OFDM technology can reduce inter-symbol interference,strong impulsive noise can greatly reduce the quality of the OFDM system.Therefore,the purpose of this paper is to achieve the high-precision channel estimation and interference(impulsive noise)cancellation in UA communication systems.Specifically,this article mainly includes the following four aspects of innovative work:First,using the sparsity of underwater acoustic channel response and impulsive noise,a sparse Bayesian learning(SBL)algorithm based on expectation maximization(EM)algorithm for joint channel estimation and impulsive noise cancellation algorithm in UA OFDM systems is proposed.Second,considering the time-varying characteristics of underwater acoustic channels,the SBL algorithm is combined with forward-backward Kalman filters to propose a joint time-varying channel tracking and impulsive noise estimation algorithm.Third,in order to further improve system performance,under the condition of limited spectrum resources of underwater acoustic OFDM systems,a joint symbol detection and channel and impulsive noise estimation algorithm using all subcarrier information is proposed.Fourth,on the basis of the above research,a joint symbol detection and time-varying channel tracking algorithm is designed by combining the SBL algorithm and the Kalman filter and using all carrier information.The performance of our proposed algorithms is verified through both numerical simulations and by data collected during a UA communication experiment conducted in the estuary of the Swan River,Perth,Australia.The results demonstrate that compared with existing approaches,the proposed algorithms achieve a better system bit-error-rate and frame-error-rate performance.