Improving The Channel Estimation In OFDM System Using Fuzzy Logic And ANN In Parallel

Abstract

This paper introduces a method for developing the detection in OFDM system using Estimation channel by FL (Fuzzy Logic) and ANN (Artificial Neural Network) in Parallel. OFDM system and OFDM with FL-ANN (OFDM-FL-ANN) are explained in details and are modeled using matlab Simulink. BER (Bit Error Rate) is calculated to comparing among OFDM and OFDM-FL-ANN performance. Detection is improved by estimation channel using FL-ANN. The ANN part estimates the noise of channel to cancel the noise. While the fuzzy logic part estimates channel state of information. OFDM-FL-ANN has better performance. BER is founded for improved OFDM system with FL-ANN and OFDM to compare. The results indicate that proposed method improves detection in OFDM system, where the average of enhancement rate for BER is 40.011 and 0.55 Mbps for both BER, throughput. Finally, as implementation case, "Queen Elizabeth's" image is sent and received using OFDM and OFDM-FL-ANN models in MatLab Simulink. The average of enhancement 10.8291 in MSE for OFDM-FL-ANN over the basic OFDM model.