Document Type
Article
Publication Date
2003
Abstract
This paper presents a neural decoder for trellis coded modulation (TCM) schemes. Decoding is performed with Radial Basis Function Networks and Multi-Layer Perceptrons. The neural decoder effectively implements an adaptive Viterbi algorithm for TCM which learns communication channel imperfections. The implementation and performance of the neural decoder for trellis encoded 16-QAM with amplitude imbalance are analyzed.
Journal Name
Engineering Applications of Artificial Intelligence
Recommended Citation
Kaminsky, Edit J., and Nikhil Deshpande, “TCM Decoding using Neural Networks,” Engineering Applications of Artificial Intelligence, Vol 16, no. 5-6, Aug.-Sept., 2003, pp. 473-489.
Comments
This is a pre-copy-editing, author-produced PDF of an article accepted for publication. doi: 10.1016/S0952-1976(03)00066-6
Copyright 2003, Elsevier, Ltd. All rights reserved.