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Conference papers

Low-complexity Computational Units for the Local-SOVA Decoding Algorithm

Abstract : Recently the Local-SOVA algorithm was suggested as an alternative to the max-Log MAP algorithm commonly used for decoding Turbo codes. In this work, we introduce new complexity reductions to the Local-SOVA algorithm, which allow an efficient implementation at a marginal BER penalty of 0.05 dB. Furthermore, we present the first hardware architectures for the computational units of the Local-SOVA algorithm, namely the add-compare select unit and the soft output unit of the Local-SOVA for radix orders 2, 4 and 8 were proposed. We provide place & route implementation results for 28nm technology and demonstrate an area reduction of 46 − 75% for the soft output unit for radix orders ≥ 4 in comparison with the respective max-Log MAP soft output unit. These area reductions compensate for the overhead in the add compare select unit, resulting in overall area saving of around 27 − 46% compared to the max-Log-MAP. These savings simplify the design and implementation of high throughput Turbo decoders.
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https://hal.archives-ouvertes.fr/hal-02545582
Contributor : Stefan Weithoffer Connect in order to contact the contributor
Submitted on : Tuesday, May 12, 2020 - 12:22:41 PM
Last modification on : Monday, April 4, 2022 - 9:28:19 AM

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Stefan Weithoffer, Rami Klaimi, Charbel Abdel Nour, Norbert Wehn, Catherine Douillard. Low-complexity Computational Units for the Local-SOVA Decoding Algorithm. PIMRC 2020: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications - ETTCOM Workshop, Aug 2020, London (Virtual), United Kingdom. ⟨10.1109/PIMRC48278.2020.9217318⟩. ⟨hal-02545582v4⟩

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