Intelligent Adaptive Equalizer Design Using Nature Inspired Algorithms

In a message transferring scheme, signal has been transmitted through a noisy communication channel. As a result distorted signal is generated due to Inter Symbol Interference (ISI). To overcome this limitation the most suitable resolution is utilization of Adaptive Equalizers (AEs) in an efficient manner. Moreover, reduction of noise as well as ISI have been accomplished by tuning the parameters of the AEs without having any erstwhile knowledge about the clamor. Hence, the inevitability of conniving competent AE has been appeared as one of the thought-provoking areas of study since 1975. Meanwhile, the performances of the traditional AEs have also been enriched by using numerous proficient meta-heuristic algorithms. By considering the above facts an endeavor has been prepared to design various well-organized AEs triggered by nature inspired algorithms. In this article, the meta-heuristic algorithms named Artificial Bees Colony (ABC), Ant Colony Optimization (ACO) and Cuttlefish Algorithm (CA) have been considered for adjustment of filter co-efficient in an optimum manners. Additionally, an in-depth investigation has been executed to evaluate the performance of the proposed skills in terms of convergence nature and Bit Error Rate (BER). In this regard, two existing conventional techniques i.e. Least Mean Square (LMS) Algorithm and Constant Modulus Algorithm (CMA) have been well thought out for the purpose of comparison. In addition, behavior of the projected AEs has also been analyzed under numerous fading environments. Ultimately, the acts of the projected AEs have been assessed in advanced communication system.