A Closed Form Expression for the Exact Bit Error Probability for Viterbi Decoding of Convolutional Codes
Abstract
In 1995, Best et al. published a formula for the exact bit error probability for Viterbi decoding of the rate R=1/2, memory m=1 (2-state) convolutional encoder with generator matrix G(D)=(1 1+D) when used to communicate over the binary symmetric channel. Their formula was later extended to the rate R=1/2, memory m=2 (4-state) convolutional encoder with generator matrix G(D)=(1+D^2 1+D+D^2) by Lentmaier et al. In this paper, a different approach to derive the exact bit error probability is described. A general recurrent matrix equation, connecting the average information weight at the current and previous states of a trellis section of the Viterbi decoder, is derived and solved. The general solution of this matrix equation yields a closed form expression for the exact bit error probability. As special cases, the expressions obtained by Best et al. for the 2-state encoder and by Lentmaier et al. for a 4-state encoder are obtained. The closed form expression derived in this paper is evaluated for various realizations of encoders, including rate R=1/2 and R=2/3 encoders, of as many as 16 states. Moreover, it is shown that it is straightforward to extend the approach to communication over the quantized additive white Gaussian noise channel.
Keywords
Cite
@article{arxiv.1111.3820,
title = {A Closed Form Expression for the Exact Bit Error Probability for Viterbi Decoding of Convolutional Codes},
author = {Irina E. Bocharova and Florian Hug and Rolf Johannesson and Boris D. Kudryashov},
journal= {arXiv preprint arXiv:1111.3820},
year = {2015}
}
Comments
9 pages, 9 figures, submitted to IEEE Transactions on Information Theory in November 2011, revised version