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Low Complexity Non-binary Turbo Decoding based on the Local-SOVA Algorithm

Hugo Le Blevec 1 Rami Klaimi 1, 2 Stefan Weithoffer 1, 3 Charbel Abdel Nour 1, 2 Amer Baghdadi 1, 3
2 Lab-STICC_CODES - Equipe CODES
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance : UMR6285
3 Lab-STICC_2AI - Equipe Algorithm Architecture Interactions
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance : UMR6285
Abstract : Non-binary Turbo codes have been shown to outperform their binary counterparts in terms of error correcting performance yet the decoding complexity of the commonly used Min-Log-MAP algorithm prohibits efficient hardware implementations. In this work, we apply for the first time the recently proposed Local SOVA algorithm for decoding non-binary Turbo codes. Moreover, we propose a low complexity variant dedicated to the direct association with high order constellations denoted by the nearest neighbor Local SOVA. It considers only a limited amount of nearest competing constellation symbols for the soft output computation. Simulation results show that this approach allows a complexity reduction of up to 52% in terms of add-compare-select operations while maintaining the same error correcting performance compared to the Min-Log-MAP algorithm. It can even reach up to 80% if high code rates or frame error rates higher than 10^(−4) are targeted. The achieved complexity reduction represents a significant step forward towards hardware implementation.
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https://hal-imt-atlantique.archives-ouvertes.fr/hal-03279861
Contributor : Rami Klaimi <>
Submitted on : Tuesday, July 6, 2021 - 5:34:45 PM
Last modification on : Thursday, July 29, 2021 - 10:51:11 AM

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  • HAL Id : hal-03279861, version 1

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Hugo Le Blevec, Rami Klaimi, Stefan Weithoffer, Charbel Abdel Nour, Amer Baghdadi. Low Complexity Non-binary Turbo Decoding based on the Local-SOVA Algorithm. ISTC 2021: 11th IEEE International Symposium on Topics in Coding, Aug 2021, Montreal, Canada. ⟨hal-03279861⟩

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