Research On EMD-ICA Joint Adaptive Denoising Algorithm For Indoor Visible Light Communications

With the development of light-emitting Diode(LED)and other new lighting technologies,Visible Light Communication(VLC),as a promising new Communication technology in the field of wireless Communication,provides a new solution for indoor high-speed Communication.However,due to the complexity of noise components,indoor visible light communication has serious noise interference problem,which will cause communication performance damage.Therefore,it is of great significance for the development of indoor visible light communication technology to study the appropriate noise suppression algorithm to improve the influence of noise on the performance of communication system.For this reason,this thesis mainly studies the noise reduction of indoor visible light communication system.The main work includes:(1)Indoor visible light communication based on the actual application scenario is perfect communication system model is set up,established a direct line-of-sight link and diffuse multipath transmission channel model of line-of-sight link,based on detailed analysis of the noise of the indoor visible light communication system components and related spectrum characteristics,as to provide theoretical basis for discussion and noise suppression algorithm is designed.(2)In order to solve the Noise interference problem of indoor visible light communication,a combined Noise reduction algorithm based on the modal correlation criterion,Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Independent Component Analysis(ICA)was proposed.Compared with the traditional VLC denoising algorithm,the CEEMDAN-ICA joint denoising algorithm has better denoising effect and higher signal integrity by taking advantage of the feature that CEEMDAN-ICA can decompose signals adaptive and the feature that ICA can extract useful information from complex signals.After comparing and analyzing the noise reduction effect of different noise reduction algorithms under different SNR conditions,the simulation results show that the CEEMDAN-ICA joint noise reduction algorithm can effectively reduce the influence of noise interference on the signal and improve the communication performance.However,under the condition of small SNR,the modal correlation criterion has the problem of algorithm instability.(3)In view of the fact that the modal correlation criterion is not suitable for the accurate discrimination of noise layer and signal layer under the condition of low SNR,a joint denoising method of CEEMDAN-ICA based on the sample entropy criterion is proposed.Compared with the modal correlation criterion,the sample entropy criterion is based on the complexity of the signal to distinguish the noise and signal,which has better robustness and higher stability.The simulation results show that the joint denoising algorithm based on the sample entropy criterion can distinguish the noise layer and the signal layer more effectively in the low SNR,which improves the robustness and stability of the joint denoising algorithm.To sum up,this thesis proposes and introduces the joint noise reduction algorithm based on CEEMDAN-ICA for indoor visible light communication system noise interference.The simulation results show that when the received input SNR is-5d B,the noise reduction effect of CEEMDAN-ICA based on the modal correlation criterion is superior,and the SNR is increased to 7.8d B,the root mean square error is reduced to 0.4,the correlation coefficient is 0.92,and the noise reduction gain is 12.8d B.When the SNR condition is 1d B,the SNR is increased to12.3d B,the root mean square error is 0.3,the correlation coefficient can reach 0.97,and the noise reduction gain is 11.3d B.For the combined denoising method based on the sample entropy criterion,when the received input SNR is-5d B,the SNR can be increased to 8.8d B,the denoising gain can reach 13.8d B,and the root mean square error is less than 0.4,and the correlation coefficient can reach 0.93.The comprehensive research results show that the joint noise suppression method based on CEEMDAN-ICA in this thesis can effectively filter noise and improve communication quality under different SNR conditions,and has a good performance.