Design of improved Adaptive Equalizers using intelligent computational techniques: Extension to WiMAX system

During transmission of signal through a channel the signal becomes distorted noise and the transmitted signal also suffers from Inter Symbol Interference (ISI). Adaptive Equalizers (AEs) are used to reduce the ISI and the noise by updating the filter coefficients without having the prior information about the noise. So the necessity of designing more efficient adaptive filters has been emerged as one of the interesting research areas over last decades. In recent past some optimization techniques have been developed which provide better results than conventional Adaptive Equalizers (AEs). In this context, an attempt has been made to explore some efficient AEs based on the intelligent computational techniques. Three optimization techniques namely Harmony Search (HS), Cuckoo Search (CS) and Flower Pollination Algorithm (FPA) have been used in this paper. Moreover, the comparative analysis of the convergence behavior and BER performances of the proposed AEs have been investigated and also compared with Least Mean Square (LMS) Algorithms and Constant Modulus Algorithms (CMA) based AEs. Furthermore, performance analysis of the proposed AEs under different fading channel conditions like Rayleigh, Rician and Nakagami Fading have also been studied. Finally, the performances of the proposed equalizers have been evaluated in WiMAX system.