Channel Equalization Using Multilayer Perceptron Networks

ABSTRACT In most digital communication systems, bandwidth limited channel along with multipath propagationcauses ISI (Inter Symbol Interference) to occur. This phenomenon causes distortion of the given transmittedsymbol due to other transmitted symbols. With the help of equalization ISI can be reduced. This paperpresents a solution to the ISI problem by performing blind equalization using ANN (Artificial NeuralNetworks). The simulated network is a multilayer feedforward Perceptron ANN, which has been trainedby utilizing the error back-propagation algorithm. The weights of the network are updated in accordancewith training of the network. This paper presents a very effective method for blind channel equalization,being more efficient than the pre-existing algorithms. The obtained results show a visible reduction inthe noise content.Key Words: Blin d Channel Equalization, Neural Networks, Noisy Signal, Multi Layer Perceptron,Error-Back Propagation. * Assistant Professor, Department of Electronic Engineering, Mehran University of Engineering & Technology, Jamshoro.** Assistant Professor, Department of Computer Systems Engineering, Mehran University of Engineering & Technology, Jamshoro.*** Meritorious Professor, Department of Computer Systems Engineering, Mehran University of Engineering & Technology, Jamshoro

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