Improved BER Performance Using Novel ELM Based Demodulator for CAP-VLC System

Recent trends in the field of communication science show that most devices are built and governed by Visible Light Communication (VLC) and Light Emitting Diodes (LED). The communication process depends on source characteristics and bandwidth restriction, and effective methods of modulation and demodulation can enhance data rate. Attractive and practical Carrierless Amplitude-Phase (CAP) modulation is used for higher efficiency and easier implementation. However, the performance of the CAP-VLC system gets adversely affected by factors like jamming, scattering, and low sensitivity to receiver signal. Hence, this paper examines the mitigation of available system degrading factors, based on a high-speed, extreme learning machine algorithm (ELM). Prediction analysis and simulation are processed using trained raw dataset for CAP demodulation, to prove the level of performance in terms of accuracy as 92%, under various parametric conditions. This system that is proposed can achieve bit error rate (BER) of 40% to 50% of noise ratio and can be effectively used in sectors like medical health care, banking, and finance.