Visible light communication equalization method based on radial basis function neural network

Abstract

The invention discloses a visible light communication equalization method based on a radial basis function neural network. The method is used for improving bit error rate performance of the visible light communication, improving equalization algorithm convergence speed and reducing the complexity degree of the traditional neural network equalization. The method comprises the following steps: sending a signal to a receiving end from a sending end through a visible light channel, analyzing a relation between an input signal and a transmitting signal of an equalizer, accomplishing nonlinear change of the signal through a neural network implicit strata determined by a radial basis function, mapping the input to an exit layer, performing linear weighting on an implicit node output by an outputlayer and optimizing an equalizer structure; performing center vector learning by using k-mean clustering algorithm, training the neural network, and minimizing the error function; finally performingjudgment output, recovering a sending sequence, and realizing an equalization aim. The invention realizes a visible light communication equalization method based on the radial basis function neural network, the communication quality and a transmission rate of the visible light communication are improved, the training duration of the equalization algorithm is shortened, and the system complexity isreduced.

Description

technical field [0001] The present invention relates to the field of visible light communication, in particular to a visible light communication equalization method based on a radial basis function neural network. Background technique [0002] LED-based visible light communication (Visible Light Communication, VLC) technology is a broadband wireless access technology, which has the advantages of rich spectrum resources, large potential communication capacity, good confidentiality, green safety, and no license. Visible light communication integrates lighting and communication technology, which not only meets the needs of modern development of green and energy-saving, but also uses free spectrum to obtain higher data transmission rate and higher signal-to-noise ratio than traditional wireless communication systems, which can alleviate the current Radio frequency spectrum resources are increasingly scarce and other issues. As an emerging wireless communication technology, visi...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a visible light communication equalization method based on radial basis function neural network to solve the problems of limited modulation bandwidth, low transmission rate and serious inter-symbol interference in visible light communication, and to improve the traditional neural network equalization technology for visible light The convergence speed of communication reduces the complexity of its algorithm

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