Equalizer Optimization using Flower Pollination Algorithm

Transmission of information from the source to the receiver involves automatic inclusion of random errors to the signal due to noise, interference or other system imperfections. Equalizers can be fruitfully utilized to minimize this error. Since the channel condition is always dynamic, the coefficients of the equalizer have to be set in an adaptive manner. This leads to the necessity of using Adaptive Equalizer (AE) in the communication system. Efficient optimization techniques add up an extra dimension to it. In this regard, a novel Flower Pollination Algorithm (FPA) based Adaptive Equalizer (AE) has been proposed in this paper to minimize the channel errors with minimum number of iterations. The convergence behavior of the adaptive algorithm has been studied to establish the effectiveness of our proposition. Moreover, the Bit Error Rate (BER) performance of the proposed adaptive equalizer has been studied which shows considerable improvement over the entire range of SNR. Finally, the superiority of the proposed FPA optimized Adaptive Equalizer has been established over the existing techniques like Least-Mean-Square (LMS) and Constant Modulus Algorithm (CMA) based Adaptive Equalizer in terms of convergence as well as BER performance.