Near-optimal turbo decoding in presence of SNR estimation error

Optimal iterative log-MAP (LM) decoding of turbo codes requires accurate signal to noise ratio (SNR) information. In practice, there is SNR mismatch priori to decoding due to inaccurate SNR estimation. Although max-log-MAP turbo decoding avoids the detrimental effect of SNR mismatch, its performance...

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Bibliographic Details
Published in2012 IEEE Global Communications Conference (GLOBECOM) pp. 3737 - 3742
Main Authors El-Khamy, M., Jinhong Wu, Jungwon Lee, Heejin Roh, Inyup Kang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2012
Subjects
3GPP modem
log-MAP
max-log-MAP
noise variance estimation
SNR mismatch
Turbo decoding
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Summary:Optimal iterative log-MAP (LM) decoding of turbo codes requires accurate signal to noise ratio (SNR) information. In practice, there is SNR mismatch priori to decoding due to inaccurate SNR estimation. Although max-log-MAP turbo decoding avoids the detrimental effect of SNR mismatch, its performance is inferior to LM decoding at accurate SNR estimation. In this paper, we propose two architectures for improved turbo decoding in presence of SNR mismatch. The first architecture called "SNR-Mismatch Aware Turbo (SMAT) Decoder" selects the decoder with the best performance at any SNR mismatch. The second architecture called "SNR-Mismatch Compensated Turbo (SMCT) Decoder" performs accurate SNR-mismatch estimation and compensates for the mismatch while decoding. We provide symbol-based as well as bit-level LLR histogram-based approaches for SNR mismatch estimation. We show that the proposed SMCT decoder has near-optimal performance regardless of the initial SNR mismatch. We demonstrate the effectiveness of the proposed turbo decoding architectures by Monte Carlo simulations.
ISBN:1467309206
9781467309202
ISSN:1930-529X
2576-764X
DOI:10.1109/GLOCOM.2012.6503698