No Detail Found!

Channel equalization using multilayer perceptron networks.

Author(s)
Saba Baloch Department of Electronic Engineering, Mehran University of Engineering & Technology, Jamshoro, Pakistan
Javed Ali Baloch Department of Computer Systems Engineering Mehran University of Engineering & Technology, Jamshoro, Pakistan
Mukhtiar Ali Unar Department of Computer System Engineering, Mehran University of Engineering & Technology, Jamshoro, Pakistan
Abstract
In most digital communication systems, bandwidth limited channel along with multipath propagation causes ISI (Inter Symbol Interference) to occur. This phenomenon causes distortion of the given transmitted symbol due to other transmitted symbols. With the help of equalization ISI can be reduced. This paper presents a solution to the ISI problem by performing blind equalization using ANN (Artificial Neural Networks). The simulated network is a multilayer feedforward Perceptron ANN, which has been trained by utilizing the error back-propagation algorithm. The weights of the network are updated in accordance with 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 in the noise content.
Publication Details
Page(s) 469-474
DOI DOI not available
Published Journal: Mehran University Research Journal of Engineering and Technology, Volume: 31, Issue: 3, Year: 2012

Request the full text from PASTIC

More from Mehran University Research Journal of Engineering and Technology
0

Citations

0

Downloads

67

Views

Copyright ©  PASTIC National Center, Islamabad www.pastic.gov.pk