Recovery of Digital Information Using Bacterial Foraging Optimization Based Nonlinear Channel Equalizers

Transmission and storing of high density digital information plays an important role in the present age of information technology. These binary data are distorted while reading out of the recording medium or arriving at the receiver end due to inter symbol interference in the channel. The adaptive channel equalizer alleviates this distortion and reconstructs the transmitted data faithfully. The bacterial foraging optimization (BFO) is a recently developed efficient and derivative free evolutionary computing tool used for optimization purpose. In the present paper we propose a novel nonlinear channel equalizer using BFO algorithm. The recovery performance of the new equalizer is obtained through computer simulation study using nonlinear channels. It is shown that the proposed equalizer offers superior performance both in terms of bit-error-rate and convergence speed compared to the GA based equalizers. In addition it requires substantially less computation during training.