{"title":"Analysis of Joint Source Channel LDPC Coding for Correlated Sources Transmission over Noisy Channels","authors":"Marwa Ben Abdessalem, Amin Zribi, Ammar Bouall\u00e8gue","volume":123,"journal":"International Journal of Electronics and Communication Engineering","pagesStart":296,"pagesEnd":301,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10006674","abstract":"In this paper, a Joint Source Channel coding scheme
\r\nbased on LDPC codes is investigated. We consider two concatenated
\r\nLDPC codes, one allows to compress a correlated source and the
\r\nsecond to protect it against channel degradations. The original
\r\ninformation can be reconstructed at the receiver by a joint decoder,
\r\nwhere the source decoder and the channel decoder run in parallel by
\r\ntransferring extrinsic information. We investigate the performance of
\r\nthe JSC LDPC code in terms of Bit-Error Rate (BER) in the case
\r\nof transmission over an Additive White Gaussian Noise (AWGN)
\r\nchannel, and for different source and channel rate parameters.
\r\nWe emphasize how JSC LDPC presents a performance tradeoff
\r\ndepending on the channel state and on the source correlation. We
\r\nshow that, the JSC LDPC is an efficient solution for a relatively
\r\nlow Signal-to-Noise Ratio (SNR) channel, especially with highly
\r\ncorrelated sources. Finally, a source-channel rate optimization has
\r\nto be applied to guarantee the best JSC LDPC system performance
\r\nfor a given channel.","references":"[1] C. E. Shannon, \u201cA mathematical theory of communication,\u201d Bell System\r\nTechnical Journal, vol. 27, pp. 379-423, 623\u2013656, 1948.\r\n[2] S. Vembu, S. Verdu, and Y. Steinberg, \u201cThe source-channel separation\r\ntheorem revisited,\u201d IEEE Trans. on Inform. Theory, vol. 41, no. 1, pp.\r\n44\u201354, Jan. 1995.\r\n[3] T. M. Cover and J. A. Thomas, \u201cElements of Information Theory,\u201d John\r\nWiley, New York, 1991.\r\n[4] K. Sayood and J. C. Borkenhagen, \u201cUse of residual redundancy in the\r\ndesign of joint source\/channel coders,\u201d IEEE Trans. on Comm., vol. 39,\r\nno. 6, pp. 838\u2013846, June 1991.\r\n[5] A. Zribi, R. Pyndiah, S. Zaibi, F. Guilloud, and A. Bouallgue,\r\n\u201cLow-complexity soft decoding of Huffman codes and iterative joint\r\nsource\/channel decoding,\u201d IEEE Trans. on comm., vol. 60, n. 6, pp.\r\n1669\u20131679, Jun. 2012.\r\n[6] R. Bauer and J. Hagenauer, \u201cOn variable length codes for iterative\r\nsource\/channel decoding,\u201d Proc. Data Compression Conference, pp.\r\n273\u2013282, April. 2001.\r\n[7] J. Kliewer and R. Thobaben, \u201cIterative joint source\u2013channel decoding\r\nof variable length codes using residual source redundancy,\u201d IEEE Trans.\r\nWireless. Commun., vol. 4, no. 3, pp. 919\u2013929, May 2005.\r\n[8] H. Nguyen and P. Duhamel, \u201cRobust source decoding of varaible\u2013length\r\nencoded video data taking into account source constraints ,\u201d IEEE Trans.\r\nCommun., vol. 53, no. 7, pp. 1077\u20131084, Jul. 2005.\r\n[9] M. Fresia, F. Prez-Cruz, H. V. Poor, and S. Verdu, \u201cJoint source and\r\nchannel coding,\u201d IEEE Sig. Proc. Mag., vol.27, pp. 104\u2013113, Nov. 2010.\r\n[10] R. Asvadi, T. Matsumoto, and M. J. Juntti, \u201cOptimized LDPC codes for\r\njoint source-channel decoding of quantized Gauss-Markov signals,\u201d IEEE\r\nInternational Conference on Communications (ICC), pp. 5233\u20135238,\r\n2014.\r\n[11] T. Hindelang, J. Hagenauer, and S. Heinen, \u201cSources\u2013controlled channel\r\ndecoding: Estimation of correlated parameters,\u201d in Proc. 3rd Int. ITG\r\nConf. on source and channel coding, pp. 259\u2013266, Munich, Germany,\r\n2000.\r\n[12] M. A. Mohd Izhar, N. Fisal, X. Zhou, K. Anwar, and T. Matsumoto,\r\n\u201cExploitation of 2D binary source correlation using turbo block codes\r\nwith fine-tuning ,\u201d EURASIP Journal on Wireless Communications and\r\nNetworking, vol. 2013, no. 1, pp. 1\u201311, 2013. ","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 123, 2017"}