Adaptive Channel Equalization using Teaching Learning based Optimization

In digital communication channel the transmitted signal might get dispersive due to which the information may not conveyed same as transmitted. Additive noise and inter-symbol interference (ISI) cause dispersion of signal. The ISI can be minimised if the channel is precisely known. In practice, however, we seldom have prior knowledge of the channel characteristics though there is unavoidable problem of imprecision that arises in physical implementations of the filters. To compensate the intrinsic residual distortion equalization used. In this paper equalization of channel coefficients is done through evolutionary adaptive algorithms. Conventional differential evolution (DE) and particle swarm optimization (PSO) are used for equalizing second order channel. Later a new optimization technique called teaching learning based optimization (TLBO) is used which provides a better solution. In this paper a comparative study of discussed optimization techniques for different scenarios are provided.