Wavelet Transform - Artificial Neural Network Receiver with Adaptive Equalization for a Diffuse Indoor Optical Wireless OOK Link

This paper presents an alternative approach for signal detection and equalization using the continuous wavelet transform (CWT) and the artificial neural network (ANN) in diffuse indoor optical wireless links (OWL). The wavelet analysis is used for signal pre-processing (feature extraction) and the ANN for signal detection. Traditional receiver architectures based on matched filter (MF) experience significant performance degradation in the presence of artificial light interference (ALI) and multipath induced intersymbol interference (ISI). The proposed receiver structure reduces the effect of ALI and ISI by selecting a particular scale of CWT that corresponds to the desired signal and classifying the signal into binary 1 and 0 based on an observation vector. The simulation results show that the Wavelet-ANN architecture outperforms MF receiver even with the filter matched to the ISI affected pulse shape. The Wavelet-ANN receiver is also capable of providing a bit error rate (BER) performance comparable to the equalized forms of traditional receiver structure.