Iterative Decoding of Turbo Codes

  • Dhaneshwar Sah Advanced College of Engineering and Management, T.U.
Keywords: SOVA, MAP, SISO, Turbo Codes, RSC, Channel Model, SNR, BER, LLR, VA


 This paper presents a Thesis which consists of a study of turbo codes as an error-control Code and the software implementation of two different decoders, namely the Maximum a Posteriori (MAP), and soft- Output Viterbi Algorithm (SOVA) decoders. Turbo codes were introduced in 1993 by berrouet at [2] and are perhaps the most exciting and potentially important development in coding theory in recent years. They achieve near- Shannon-Limit error correction performance with relatively simple component codes and large interleavers. They can be constructed by concatenating at least two component codes in a parallel fashion, separated by an interleaver. The convolutional codes can achieve very good results. In order of a concatenated scheme such as a turbo codes to work properly, the decoding algorithm must affect an exchange of soft information between component decoders. The concept behind turbo decoding is to pass soft information from the output of one decoder to the input of the succeeding one, and to iterate this process several times to produce better decisions. Turbo codes are still in the process of standardization but future applications will include mobile communication systems, deep space communications, telemetry and multimedia. Finally, we will compare these two algorithms which have less complexity and which can produce better performance.

Journal of Advanced College of Engineering and Management, Vol.3, 2017, Page: 15-30


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How to Cite
Sah, D. (2018). Iterative Decoding of Turbo Codes. Journal of Advanced College of Engineering and Management, 3, 15-30.