Implementation of low-complexity suboptimal turbo decoders using greedy algorithms

Author

Venkat Mandagulathur Pattabhiraman

Abstract

"Turbo coding is one of the best channel coding procedures presented to the coding community in the recent history of channel coding. The efficient error correcting capability of turbo codes is attributed to its decoding method. The purpose of this thesis is to design and implement a novel decoding method which is simpler than the existing decoding methods thereby reducing the decoding complexity to a reasonable level. The novel method of decoding is based on a greedy algorithm which involves the search of proper error patterns that aims at reducing the overall global metric. This novel method is implemented for a convolutional encoder and then for the turbo encoder with both recursive and the non-recursive component structures. It is found that this new method of decoding is simpler than older methods and also gives encouraging performance"--Abstract, page iii.

Advisor(s)

Weeks, William IV

Committee Member(s)

Kosbar, Kurt Louis
Beetner, Daryl G.

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Publisher

University of Missouri--Rolla

Publication Date

Summer 2002

Pagination

viii, 62 pages

Note about bibliography

Includes bibliographical references (pages 60-61).

Rights

© 2002 Venkat Mandagulathur Pattabhiraman, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Subject Headings

Coding theory
Digital communications
Algorithms

Thesis Number

T 8132

Print OCLC #

52636046

Link to Catalog Record

Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.

Recommended Citation

Pattabhiraman, Venkat Mandagulathur, "Implementation of low-complexity suboptimal turbo decoders using greedy algorithms" (2002). Masters Theses. 2245.
https://scholarsmine.mst.edu/masters_theses/2245