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Asymptotic Distance and Convergence Analysis of Braided Protograph Convolutional Codes

Tavares, Marcos B.S. ; Lentmaier, Michael LU ; Fettweis, Gerhard and Zigangirov, Kamil LU (2008) Annual Allerton Conference on Communication, Control and Computing (Allerton), 2008 p.1073-1080
Abstract
We analyze a class of LDPC convolutional codes that are constructed from tightly braided convolutional base codes by a lifting procedure. For these braided protograph convolutional codes, we show that the distances grow linearly with the constraint length, and we present lower bounds on their asymptotic segment distance and free distance as well as on the asymptotic minimum distance of their tail-biting versions. With some constraints imposed on the lifting permutations, braided protograph convolutional codes can also be decoded as turbo-like codes by iterative application of the BCJR algorithm. For this case, we derive an explicit upper-bound on the asymptotic decoding error probability as a function of the number of iterations.
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
braided codes, braided convolutional codes, spatial coupling
host publication
[Host publication title missing]
pages
1073 - 1080
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
Annual Allerton Conference on Communication, Control and Computing (Allerton), 2008
conference location
Monticello, IL, United States
conference dates
2008-09-23 - 2008-09-26
external identifiers
  • scopus:64549123486
ISBN
978-1-4244-2925-7
DOI
10.1109/ALLERTON.2008.4797678
language
English
LU publication?
yes
id
b19b44b9-3a82-4fd8-ad19-153bd7409889 (old id 3731350)
date added to LUP
2016-04-04 11:06:49
date last changed
2022-01-29 21:20:13
@inproceedings{b19b44b9-3a82-4fd8-ad19-153bd7409889,
  abstract     = {{We analyze a class of LDPC convolutional codes that are constructed from tightly braided convolutional base codes by a lifting procedure. For these braided protograph convolutional codes, we show that the distances grow linearly with the constraint length, and we present lower bounds on their asymptotic segment distance and free distance as well as on the asymptotic minimum distance of their tail-biting versions. With some constraints imposed on the lifting permutations, braided protograph convolutional codes can also be decoded as turbo-like codes by iterative application of the BCJR algorithm. For this case, we derive an explicit upper-bound on the asymptotic decoding error probability as a function of the number of iterations.}},
  author       = {{Tavares, Marcos B.S. and Lentmaier, Michael and Fettweis, Gerhard and Zigangirov, Kamil}},
  booktitle    = {{[Host publication title missing]}},
  isbn         = {{978-1-4244-2925-7}},
  keywords     = {{braided codes; braided convolutional codes; spatial coupling}},
  language     = {{eng}},
  pages        = {{1073--1080}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Asymptotic Distance and Convergence Analysis of Braided Protograph Convolutional Codes}},
  url          = {{https://lup.lub.lu.se/search/files/5697578/3731356.pdf}},
  doi          = {{10.1109/ALLERTON.2008.4797678}},
  year         = {{2008}},
}