Channel Estimation Algorithms Based On Channel Reconstruction Compressed Sensing In DCO-OFDM Visible Light Communication System

VLC communication has the advantages of rich spectrum resources,green environmental protection,convenient deployment,good confidentiality and high transmission rate.The time domain response of the visible light channel is sparse,so the compressed sensing theory can be applied to the sparse channel estimation of the VLC system.This paper focuses on the DCO-OFDM visible light communication system,and studies the channel estimation algorithm based on compressed sensing.The main research work is as follows.Firstly,the matching pursuit channel estimation algorithm based on support set optimization of DCO-OFDM system is studied.Based on the introduction of OMP algorithm and SAMP algorithm based on compressed sensing,the deficiencies of the existing OMP algorithm and SAMP algorithm are analyzed,and an improved orthogonal matching pursuit channel estimation algorithm for DCO-OFDM system is proposed.The algorithm improves the accuracy of the support set by combining the support sets of multiple algorithms and adopting the backtracking idea.Simulation experiments verify that the proposed improved channel estimation algorithm is better than existing algorithms.Secondly,the second-order differential matching pursuit channel estimation algorithm of DCO-OFDM system is studied.Based on the analysis of the shortcomings of the existing sparsity estimation methods,an improved sparsity estimation method is proposed.Based on this method,a channel estimation algorithm based on second-order difference is proposed.The algorithm estimates the sparsity through the relationship between the change in the amplitude of the inner product vector and the number of non-zero elements of the channel time-domain response,which improves the accuracy of the sparsity estimation.Simulation experiments show that the proposed channel estimation algorithm based on second-order difference is superior to existing algorithms.Thirdly,the channel estimation algorithm based on adaptive step size in DCO-OFDM system is studied.Based on the analysis of the sparsity adjustment step size strategy of the existing sparsity adaptive estimation method,the channel estimation algorithm based on the adaptive step size is proposed.The algorithm adaptively adjusts the step size with the estimation progress,overcomes the shortcomings of the existing step adjustment strategy and improves the estimation accuracy of the algorithm.Simulation experiments show that the performance of the proposed channel estimation algorithm based on adaptive step size is better than existing algorithms.Fourthly,the channel estimation algorithm based on adaptive backtracking in DCOOFDM system is studied.Based on the analysis of the shortcomings of the backtracking strategy of the existing backtracking based channel estimation algorithm in selecting fixed atoms,a sparse channel estimation algorithm based on adaptive backtracking is proposed.By using adaptive backtracking and multiple matching strategies,the algorithm overcomes the shortcomings of the existing backtracking strategy in selecting fixed atoms,improves the accuracy of support set construction in the algorithm,and thus improves the estimation performance of the algorithm.Simulation results show that the performance of the proposed algorithm is better than existing algorithms.