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Analysis of M-Ary Modulation with M-Ary LDPC Coding for DVC

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Signal Processing and Information Technology (SPIT 2011)

Abstract

In this paper we consider the issue of Distributed Video Coding (DVC) over practical channel which involves Gaussian noisy channel. Since the research on DVC over practical channel with respect to modulation is still incomplete this paper does a comprehensive study on DVC modulation techniques to fill the gap. It discusses the suitability of M-Ary modulation to DVC on the basis of energy consumption. The study covers both theoretical and practical aspects through the practical implementation of DVC encoder and decoder, the performance in terms of bit error rate, decoder complexity and data rate of M-Ary modulation techniques used with M-Ary LDPC coding

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References

  1. Slepian, D., Wolf, J.K.: Noiseless coding of correlated information sources. IEEE Transaction on Information Theory 17-19, 47 (1973)

    MathSciNet  MATH  Google Scholar 

  2. Wyner, Ziv, J.: The Rate-distortion Function for source coding with side information at the decoder. IEEE Transaction on Information Theory 22(1), 1–10 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  3. Cappellari, L., De Giustiar, A.: A Unified Perspective, A.: on Parity- and Syndrome-Based Binary Data Compression Using Off-the-Shelf Turbo Codecs. Xiv:0902.0562v3 [cs.IT] (August 2, 2010)

    Google Scholar 

  4. Pradhan, S.S., Ramachandran, K.: Distributed source coding using syndromes (DISCUS), Design and Construction. In: Proc. IEEE DCC, pp. 158–167 (March 1999)

    Google Scholar 

  5. Wyner, A.: Recent results in the Shannon theory. IEEE Trans. Inform. Theory IT-20, 2–10 (1974)

    Article  MathSciNet  MATH  Google Scholar 

  6. Sklar, B.: Digital Communications Fundamentals and Applications, 2nd edn. Prentice Hall (January 2001)

    Google Scholar 

  7. Verdhu, S.: Spectral efficiency in wideband regime. IEEE Trans. on Information Theory 48, 1319–1343 (2002)

    Article  MathSciNet  Google Scholar 

  8. Shih, E., Cho, S.H., Rexmin, Sinha, A., Chandrakasan, A.: Physical layer driven protocol and algorithm design for energy efficient Wireless sensor networks. In: MOBICOM 2001, Rome, Italy, July 15-21 (2001)

    Google Scholar 

  9. Mukesh, S., Iqbal, M., Jianhual, Z., Ping, Z., Inam-Ur-Rehman: Comparative Analysis of M-ary Modulation Techniques for Wireless Ad-hoc Networks. In: SAS 2007 IEEE Sensor Application Symposium, San Diego, California (2007)

    Google Scholar 

  10. Davey, M., Mackay, D.: Low density parity check codes over GF(q). In: Liveris, et al. (eds.) Information theory Workshop 1998, pp. 70–71 (1998)

    Google Scholar 

  11. Thambu, K.: Wyner-Ziv Video Coding with Error-Prone Wireless Fading Channels. Crown (2010) 978-1-4244-7265-9/10/ $26.00 c_,

    Google Scholar 

  12. Tan, P., Xie, K., Li, J.: Slepian Wolf coding using parity approach and syndrome approach, 1-4244-1037-1/07/$25.00 C2007 IEEE

    Google Scholar 

  13. Xue, G., Zhang, W., Hao, C.: Syndrome based error resilience scheme of distributed joint source channel coding. In: Proceedings of ICCTA 2009 (2009)

    Google Scholar 

  14. Cappellari, L., De Giustiar, A.: Unified perspective on parity and syndrome based binary data compression using off the shelf turbo codes. Xiv 0902-0562v3 [CS-IT] (August 2, 2010)

    Google Scholar 

  15. Declereq, D., Fossorier, M.: Decoding algorithm for non binary LDPC codes over GF(q). IEEE Trans. Communication 55, 633–643 (2007)

    Article  Google Scholar 

  16. Ye, F., Men, A., Zhang, X.: An Improved Wyner-Ziv Video Coding for Sensor Network, 978-1-4244-8331- 0/11/$26.00 2011 IEEE

    Google Scholar 

  17. Distributed Image Codin. Wireless Multimedia Sensor Networks: A Survey. In: Third International Workshop on Advanced Computational Intelligence, Suzhou, Jiangsu, China, August 25-27 (2010)

    Google Scholar 

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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Masoodhu Banu, N.M., Sasikumar, S. (2012). Analysis of M-Ary Modulation with M-Ary LDPC Coding for DVC. In: Das, V.V., Ariwa, E., Rahayu, S.B. (eds) Signal Processing and Information Technology. SPIT 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32573-1_39

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  • DOI: https://doi.org/10.1007/978-3-642-32573-1_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32572-4

  • Online ISBN: 978-3-642-32573-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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