Receding horizon decoding of convolutional codes
Information Theory
2009-09-04 v1 math.IT
Optimization and Control
Abstract
Decoding of convolutional codes poses a significant challenge for coding theory. Classical methods, based on e.g. Viterbi decoding, suffer from being computationally expensive and are restricted therefore to codes of small complexity. Based on analogies with model predictive optimal control, we propose a new iterative method for convolutional decoding that is cheaper to implement than established algorithms, while still offering significant error correction capabilities. The algorithm is particularly well-suited for decoding special types of convolutional codes, such as e.g. cyclic convolutional codes.
Keywords
Cite
@article{arxiv.0909.0588,
title = {Receding horizon decoding of convolutional codes},
author = {Jose Ignacio Iglesias Curto and Uwe Helmke},
journal= {arXiv preprint arXiv:0909.0588},
year = {2009}
}