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J. Hagenauer and P. Robertson, “Iterative (“Turbo”) Decoding of Systematic Convolutional Codes with the MAP And SOVA Algorithm,” Proceedings of the ITG Tagung, Codierung für Quelle, Kanal and Ubertragung, Frankfurt, October 1994, pp. 21-29.

has been cited by the following article:

• TITLE: Performance Enhancement of SOVA Based Decoder in SCCC and PCCC Schemes

  AUTHORS: Ahmed A. Hamad

  KEYWORDS: Turbo Codes; SOVA; SCCC; Scaling Factor; EXIT

  JOURNAL NAME: Wireless Engineering and Technology, Vol.4 No.1, January 31, 2013

  ABSTRACT: This study proposes a simple scaling factor approach to improve the performance of parallel-concatenated convolutional code (PCCC) and serial concatenated convolutional code (SCCC) systems based on suboptimal soft-input soft-output (SISO) decoders. Fixed and adaptive scaling factors were estimated to mitigate both the optimistic nature of a posteriori information and the correlation between intrinsic and extrinsic information produced by soft-output Viterbi (SOVA) decoders. The scaling factors could be computed off-line to reduce processing time and implementation complexity. The simulation results show a significant improvement in terms of bit-error rate (BER) over additive white Gaussian noise and Rayleigh fading channel. The convergence properties of the suggested iterative scheme are assessed using the extrinsic information transfer (EXIT) chart analysis technique.