Low Complexity Non-binary Turbo Decoding based on the Local-SOVA Algorithm - Archive ouverte HAL Access content directly
Conference Papers Year :

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

(1) , (1, 2) , (1, 3) , (1, 2) , (1, 3)
1
2
3

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.
Fichier principal
Vignette du fichier
A_new_approach_to_Non_binary_Turbo_Decoding_based_on_the_Local_SOVA_Decoding_Algorithm.pdf (398.66 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03279861 , version 1 (06-07-2021)

Identifiers

Cite

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 International Symposium on Topics in Coding, Aug 2021, Montreal, Canada. ⟨10.1109/ISTC49272.2021.9594236⟩. ⟨hal-03279861⟩
118 View
77 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More