By Topic

A Simple parallel dual code decoding algorithm for convolutional codes with high throughput and low latency

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yu Liao ; Dept. of Electr. & Comput. Eng., Minnesota Univ., MN, USA ; J. C. Kieffer

A highly parallel maximum a posteriori (MAP) decoding algorithm is proposed for high code rate, R = (n-1)/ n , ordinary (nonpunctured) convolutional codes using trellises of reciprocal dual convolutional codes. The advantages of this approach include a substantial reduction of decoding latency and decoding complexity, and a substantial increase of decoding throughput. Applying the proposed parallel decoding algorithm to a class of serial concatenation codes that consist of high rate ordinary convolutional codes, over additive white Gaussian noise (AWGN) channels, good bit error rate (BER) and block error rate performance, comparable to that of turbo codes and low density parity check (LDPC) codes, can be obtained with smaller overall decoding complexity than that of LDPC codes.

Published in:

Information Theory, 2004. ISIT 2004. Proceedings. International Symposium on

Date of Conference:

27 June-2 July 2004