Title :
Improved bounds on convolutional code performance
Author :
Akkor, Gün ; Arikan, Ekdal
Author_Institution :
Dept. ECE, Maryland Univ., College Park, MD, USA
Abstract :
Two new bounds on the error probability of maximum-likelihood decoding of binary convolutional codes are proposed. The first bound is an extension of the ideas presented in Viterbi et al. (1998) to convolutional codes. The second bound improves the union bound by avoiding the over-counting of error events. Comparison with simulations show that the bounds provide significant improvement over classical union bound
Keywords :
binary codes; convolutional codes; error statistics; maximum likelihood decoding; binary convolutional codes; convolutional code performance; error probability bounds; maximum-likelihood decoding; union bound; AWGN; Additive white noise; Block codes; Convolutional codes; Educational institutions; Error probability; H infinity control; Maximum likelihood decoding; Testing; Viterbi algorithm;
Conference_Titel :
Information Theory, 2001. Proceedings. 2001 IEEE International Symposium on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7123-2
DOI :
10.1109/ISIT.2001.936019
