An adaptive channel equalizer using Bacterial Foraging oriented by Particle Swarm Optimization strategy

Transmission of high density digital information plays an important role in the present age of communication and information technology. These data are distorted while arriving at the receiver end due to inter symbol interference (ISI) in the channel. The adaptive channel equalizer alleviates this distortion and reconstructs the transmitted data faithfully. In recent years the area of Bacterial Foraging Optimization (BFO) has drawn attention of many researchers due to its broad applicability to different fields. In this paper, the proposed algorithm combines the foraging mechanism of E-coli bacterium introduced in Bacterial Foraging Algorithm (BFA) with the swarming pattern of birds in block introduced in Particle Swarm Optimization (PSO).It incorporates the merits of the two bio-inspired algorithms to update the weights of the equalizer. Simulation study has been carried out to show superior performance of the proposed equalizer compared to that offered by least mean square (LMS) algorithm and genetic algorithm (GA) based training.