Reduced complexity turbo decoders

Nawaz, Yassir (2003) Reduced complexity turbo decoders. Masters thesis, Memorial University of Newfoundland.

[img] [English] PDF - Accepted Version
Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.

Download (2627Kb)

Abstract

Turbo codes are a class of forward error correction codes, which have outperformed all the previously known error coding schemes. The strength of this scheme lies in the parallel concatenation of component codes and their iterative decoding algorithm. Although turbo codes have found their way in a number of future wireless communications standards, their efficient implementation in hardware and software is still being actively researched. This study therefore focuses on the design of efficient turbo decoders. The dissertation begins with the description of encoding and decoding of turbo codes. Sliding window implementations of decoding algorithms, which are used to reduce the memory requirements in turbo decoders, are presented. The contribution of this work is the proposed modifications to the conventional sliding window implementations of SOVA, bi-directional SOVA and Max-Log-MAP based turbo decoders. The proposed modifications allow multiple bits to be released in a single decoding window thus reducing the computational complexity and increasing the decoding speed of turbo decoders. A performance and complexity comparison of these decoder implementations is also presented.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/11125
Item ID: 11125
Additional Information: Bibliography: leaves 94-96.
Department(s): Engineering and Applied Science, Faculty of
Date: 2003
Date Type: Submission
Library of Congress Subject Heading: Error-correcting codes (Information theory)

Actions (login required)

View Item View Item

Downloads

Downloads per month over the past year

View more statistics