Journal article Open Access

Revisiting the Max-Log-Map algorithm with SOVA updates rules: new simplifications for high-radix SISO decoders

Le, Vinh Hoang Son; Abdel Nour, Charbel; Boutillon, Emmanuel; Douillard, Catherine


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    <dct:title>Revisiting the Max-Log-Map algorithm with SOVA updates rules: new simplifications for high-radix SISO decoders</dct:title>
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    <dcat:keyword>convolutional codes</dcat:keyword>
    <dcat:keyword>oft-input soft-ouput decoding</dcat:keyword>
    <dcat:keyword>soft-ouput Viterbi algorithm</dcat:keyword>
    <dcat:keyword>high-radix decoding</dcat:keyword>
    <dcat:keyword>turbo codes</dcat:keyword>
    <dcat:keyword>high throughput</dcat:keyword>
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    <dct:description>&lt;p&gt;This paper proposes a new soft-input soft-output&amp;nbsp;decoding algorithm particularly suited for low-complexity highradix&amp;nbsp;turbo decoding, called local soft-output Viterbi algorithm&amp;nbsp;(local SOVA). The local SOVA uses the forward and backward&amp;nbsp;state metric recursions just as the conventional Max-Log MAP (MLM) algorithm does, and produces soft outputs&amp;nbsp;using the SOVA update rules. The proposed local SOVA exhibits&amp;nbsp;a lower computational complexity than the MLM algorithm&amp;nbsp;when employed for high-radix decoding in order to increase&amp;nbsp;throughput, while having the same error correction performance&amp;nbsp;even when used in a turbo decoding process. Furthermore, with&amp;nbsp;some simplifications, it offers various trade-offs between error&amp;nbsp;correction performance and computational complexity. Actually,&amp;nbsp;employing the local SOVA algorithm for radix-8 decoding of the&amp;nbsp;LTE turbo code reduces the complexity by 33% without any&amp;nbsp;performance degradation and by 36% with a slight penalty of&amp;nbsp;only 0.05 dB. Moreover, the local SOVA algorithm opens the door&amp;nbsp;for the practical implementation of turbo decoders for radix-16&amp;nbsp;and higher.&lt;/p&gt;</dct:description>
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