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Study on the GA-Based Decoding Algorithm for Convolutional Turbo Codes

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Advances in Neural Networks – ISNN 2009 (ISNN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5552))

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Abstract

A new decoding algorithm for convolutional Turbo codes that is called the Soft-Output Genetic Algorithm (SOGA) is proposed. With good individuals’ diversity, wide searching region and global optimizing ability, the SOGA performs better than the Soft-Output MA in terms of BER (Bit Error Rate) with the similar complexity. Simulation results show that when 1/3 code rate, 16-state convolutional Turbo codes are decoded, at BER=10− 5, the SOGA achieves about 0.2dB gains over the SOMA algorithm and nearly performs the same as the SOVA when BER<10− 4. Besides, the SOGA only deals with M states in the total 2v states, so it can save 2v-M registers compared with the SOVA when 1 bit is decoded.

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References

  1. Berrou, C., Glavieux, A., Thitimajshima, P.: Near Shannon Limit Error-correcting Coding and Decoding: Turbo-codes. In: Proc. of IEEE ICC 1993, Geneva, Switzerland, pp. 1064–1070 (1993)

    Google Scholar 

  2. Berrou, C., Glavieux, A.: Near Optimum Error Correcting Coding and Decoding: Turbo-Codes. IEEE Trans. Commun. 44, 1261–1271 (1996)

    Article  Google Scholar 

  3. Hagenauer, J., Papke, L.: Decoding Turbo-Codes with the Soft Output Viterbi Algorithm (SOVA). In: Proc. of IEEE Int. Symp. Inform. Theory, Trondheim, Norway, p. 164 (1994)

    Google Scholar 

  4. Woodard, J.P., Hanzo, L.: Comparative Study of Turbo Decoding Techniques: an Overview. IEEE Trans. Vehicular Tech. 49, 2208–2233 (2000)

    Article  Google Scholar 

  5. Park, S.J.: Combined Max-Log-MAP and Log-MAP of Turbo Codes. Electronics Lett. 40, 251–252 (2004)

    Article  Google Scholar 

  6. Wong, K.Y., McLane, P.J.: Bi-Directional Soft-Output M-Algorithm for Iterative Decoding. In: Proc. of IEEE Int. Commun., Piscataway, New Jersey, pp. 792–797 (2004)

    Google Scholar 

  7. Holland, J.H.: Adaptation in Nature and Artificial System. MIT Press, USA (1992)

    Google Scholar 

  8. Durand, N., Alliot, J.M., Bartolome, B.: Turbo Codes Optimization Using Genetic Algorithms. In: Proc. of 1999 Congress on Evolutionary Computation, Washington, DC, USA, pp. 816–822 (1999)

    Google Scholar 

  9. Chen, J., Sun, S., Wang, X., Cao, Z.: Fast Decoding of Convolutional Codes Using Genetic Algorithm. Chinese Journal of Electronics 28, 137–139 (2000)

    Google Scholar 

  10. Cardoso, F.A.C.M., Arantes, D.S.: Genetic Decoding of Linear Block Codes. In: Proc. of 1999 Congress on Evolutionary Computation, Washington, DC, USA, pp. 2302–2309 (1999)

    Google Scholar 

  11. Chen, J., Sun, S., Wang, X.: Fast Soft Decision Decoding Using Genetic Algorithm. Journal on Communications 21, 34–38 (2000)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electronic and Communications Engineering, Sun Yat-sen University, Guangzhou, Guangdong, 510275, China

    Xingcheng Liu, Shishuang Zhang & Zerong Deng

Authors
  1. Xingcheng Liu
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  2. Shishuang Zhang
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  3. Zerong Deng
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático,, CINVESTAV-IPN,, A.P. 14-740, Av.IPN 2508,, D.F., 07360,, México, México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering,, Stevens Institute of Technology,, NJ 07030,, Hoboken,, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering,, South Dakota School of Mines & Technology,, 501 E. St. Joseph Street,, SD 57701,, Rapid City,, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Liu, X., Zhang, S., Deng, Z. (2009). Study on the GA-Based Decoding Algorithm for Convolutional Turbo Codes. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_60

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  • DOI: https://doi.org/10.1007/978-3-642-01510-6_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01509-0

  • Online ISBN: 978-3-642-01510-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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