ChinaCom2009-Signal Processing for Communications Symposium

Research Article

Multi-ary SOVA Decoding Algorithm for Unitary Space-Time Symbol-Based Turbo Code

  • @INPROCEEDINGS{10.1109/CHINACOM.2009.5339930,
        author={Dapeng Zhang and Ju Liu and Lina Zheng and Hongbo Yuan},
        title={Multi-ary SOVA Decoding Algorithm for Unitary Space-Time Symbol-Based Turbo Code},
        proceedings={ChinaCom2009-Signal Processing for Communications Symposium},
        publisher={IEEE},
        proceedings_a={CHINACOM2009-SPC},
        year={2009},
        month={11},
        keywords={},
        doi={10.1109/CHINACOM.2009.5339930}
    }
    
  • Dapeng Zhang
    Ju Liu
    Lina Zheng
    Hongbo Yuan
    Year: 2009
    Multi-ary SOVA Decoding Algorithm for Unitary Space-Time Symbol-Based Turbo Code
    CHINACOM2009-SPC
    IEEE
    DOI: 10.1109/CHINACOM.2009.5339930
Dapeng Zhang1,*, Ju Liu2,*, Lina Zheng3,*, Hongbo Yuan3,*
  • 1: School of Information Science and Engineering, Shandong University, Jinan 250100, China Xidian University, Xi’an 710071, China
  • 2: School of Information Science and Engineering, Shandong University, Jinan 250100, China
  • 3: The First Aeronautical College of the Air Force, Xinyang 464000, China
*Contact email: dpzhang@sdu.edu.cn, juliu@sdu.edu.cn, zhenglina@sdu.edu.cn, hongbo_yuan@163.com

Abstract

Unitary space-time (UST) symbol-based turbo code has recently been proposed which can reduce the system complexity and calculation amount compared with bit-wise concatenation scheme. However, the corresponding maximum a posteriori (MAP) decoding algorithm still makes hardware unbearable and later its simplified versions, Max-Log-MAP and Log-MAP algorithms, appeared. In this paper, we propose a multi-ary soft output Viterbi algorithm (SOVA) decoding algorithm for UST symbol-based turbo code. Using our UST symbol-based SOVA, soft output information from the prior iteration can be accepted as the a priori information for current iteration. Notably, the experimental results show that our algorithm can achieve close performance to Max-Log-MAP and Log-MAP algorithms with lower complexity. The performance of the SOVA and that of MAP algorithm are almost the same at a BER of 10¡5, and is even better for a higher BER.