Abstract
Decision feedback equalizers (DFE)s are used extensively in practical communication systems. They are more powerful than linear equalizers especially for severe inter-symbol interference (ISI) channels with deep frequency null. In this paper, radial basis function (RBF) network is used to implement DFE. Advantages and problems of this system are discussed and its results are then compared with DFE using multilayer perception net (MLP). Results indicate that the implemented system outperforms both the least-mean square (LMS) algorithm and MLP given the same signal-to-noise ratio.
| Original language | English |
|---|---|
| Pages (from-to) | 257-267 |
| Number of pages | 11 |
| Journal | Journal of King Saud University, Engineering Sciences |
| Volume | 12 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2000 |
Bibliographical note
Publisher Copyright:© 2000 (A.H. 1420) King Saud University
Keywords
- ISI channels
- Nonlinear equalization
- decision feedback equalizers
- neural networks
- radial basis function
ASJC Scopus subject areas
- Catalysis
- Environmental Engineering
- Civil and Structural Engineering
- Renewable Energy, Sustainability and the Environment
- Materials Science (miscellaneous)
- General Chemical Engineering
- Fuel Technology
- Mechanical Engineering
- Fluid Flow and Transfer Processes
- Computer Networks and Communications
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering