Robust stopping criterion in signal-to-noise ratio uncertainty environment

A robust stopping criterion (called online-BER [OB]) that can terminate iterative turbo decoding in a signal-to-noise ratio (SNR) uncertainty environment is proposed. OB is based on the online bit error rate (BER) estimation and the BER thresholds. Both values are used to detect convergence and non-...

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Bibliographic Details
Published in:Electronics letters 2015-11, Vol.51 (23), p.1875-1877
Main Authors: Mohamad, R, Harun, H, Mokhtar, M, Adnan, W.A.W, Dimyati, K
Format: Article
Language:English
Subjects:
average iteration number reduction
BER estimation
Convergence
convergence decoder detection
Criteria
Decoders
Decoding
error statistics
Information and communications
iterative decoding
iterative turbo decoding
nonconvergence decoder detection
Online
online bit error rate estimation
robust stopping criterion
Signal to noise ratio
signal‐to‐noise ratio uncertainty environment
SNR
Thresholds
turbo codes
Uncertainty
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Summary:A robust stopping criterion (called online-BER [OB]) that can terminate iterative turbo decoding in a signal-to-noise ratio (SNR) uncertainty environment is proposed. OB is based on the online bit error rate (BER) estimation and the BER thresholds. Both values are used to detect convergence and non-convergence decoder output and also to halt iterative decoding in various SNRs. Unlike other well-known stopping criteria, OB does not depend on SNR information in its stopping rules and hence it is less complex. OB is also more robust than other stopping criteria in a SNR uncertainty environment while being capable of reducing the average iteration number and resulting in less degradation in BER performance.
ISSN:0013-5194
1350-911X
1350-911X
DOI:10.1049/el.2015.0908