Error Propagation Mitigation in Sliding Window Decoding of Braided Convolutional Codes
(2020) In IEEE Transactions on Communications 68(11). p.6683-6698- Abstract
We investigate error propagation in sliding window decoding of braided convolutional codes (BCCs). Previous studies of BCCs have focused on iterative decoding thresholds, minimum distance properties, and their bit error rate (BER) performance at small to moderate frame length. Here, we consider a sliding window decoder in the context of large frame length or one that continuously outputs blocks in a streaming fashion. In this case, decoder error propagation, due to the feedback inherent in BCCs, can be a serious problem. To mitigate the effects of error propagation, we propose several schemes: a window extension algorithm where the decoder window size can be extended adaptively, a resynchronization mechanism where we reset the encoder... (More)
We investigate error propagation in sliding window decoding of braided convolutional codes (BCCs). Previous studies of BCCs have focused on iterative decoding thresholds, minimum distance properties, and their bit error rate (BER) performance at small to moderate frame length. Here, we consider a sliding window decoder in the context of large frame length or one that continuously outputs blocks in a streaming fashion. In this case, decoder error propagation, due to the feedback inherent in BCCs, can be a serious problem. To mitigate the effects of error propagation, we propose several schemes: a window extension algorithm where the decoder window size can be extended adaptively, a resynchronization mechanism where we reset the encoder to the initial state, and a retransmission strategy where erroneously decoded blocks are retransmitted. In addition, we introduce a soft BER stopping rule to reduce computational complexity, and the tradeoff between performance and complexity is examined. Simulation results show that, using the proposed window extension algorithm, resynchronization mechanism, and retransmission strategy, the BER performance of BCCs can be improved by up to four orders of magnitude in the signal-to-noise ratio operating range of interest, and the soft BER stopping rule can be employed to reduce computational complexity.
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- author
- Zhu, Min ; Mitchell, David G.M. ; Lentmaier, Michael LU ; Costello, Daniel J. and Bai, Baoming
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Braided convolutional codes, decoder error propagation, resynchronization, retransmission, sliding window decoding, window extension
- in
- IEEE Transactions on Communications
- volume
- 68
- issue
- 11
- pages
- 16 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85096688781
- ISSN
- 0090-6778
- DOI
- 10.1109/TCOMM.2020.3015945
- language
- English
- LU publication?
- yes
- id
- f5207bc0-c78c-4aa1-869a-964080225352
- date added to LUP
- 2020-12-07 10:03:07
- date last changed
- 2022-05-12 08:23:20
@article{f5207bc0-c78c-4aa1-869a-964080225352,
abstract = {{<p>We investigate error propagation in sliding window decoding of braided convolutional codes (BCCs). Previous studies of BCCs have focused on iterative decoding thresholds, minimum distance properties, and their bit error rate (BER) performance at small to moderate frame length. Here, we consider a sliding window decoder in the context of large frame length or one that continuously outputs blocks in a streaming fashion. In this case, decoder error propagation, due to the feedback inherent in BCCs, can be a serious problem. To mitigate the effects of error propagation, we propose several schemes: a window extension algorithm where the decoder window size can be extended adaptively, a resynchronization mechanism where we reset the encoder to the initial state, and a retransmission strategy where erroneously decoded blocks are retransmitted. In addition, we introduce a soft BER stopping rule to reduce computational complexity, and the tradeoff between performance and complexity is examined. Simulation results show that, using the proposed window extension algorithm, resynchronization mechanism, and retransmission strategy, the BER performance of BCCs can be improved by up to four orders of magnitude in the signal-to-noise ratio operating range of interest, and the soft BER stopping rule can be employed to reduce computational complexity. </p>}},
author = {{Zhu, Min and Mitchell, David G.M. and Lentmaier, Michael and Costello, Daniel J. and Bai, Baoming}},
issn = {{0090-6778}},
keywords = {{Braided convolutional codes; decoder error propagation; resynchronization; retransmission; sliding window decoding; window extension}},
language = {{eng}},
number = {{11}},
pages = {{6683--6698}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Communications}},
title = {{Error Propagation Mitigation in Sliding Window Decoding of Braided Convolutional Codes}},
url = {{http://dx.doi.org/10.1109/TCOMM.2020.3015945}},
doi = {{10.1109/TCOMM.2020.3015945}},
volume = {{68}},
year = {{2020}},
}