Reliable Wireless Communication for Medical Devices Using Turbo Convolution Code

DOI: 10.4236/ijcns.2010.38094   PDF   HTML     4,764 Downloads   8,692 Views   Citations


Wireless technology is now being used to bring significantly innovative products and services in the healthcare sector, enabling new medical sensors, and treatment methods. In this paper, a new and improved communication system for communicating signals among different medical devices and a console is presented. Considering the need for very high degree of functional reliability of communication link in RF challenged environment (indoor), a novel algorithm called bi-directional “Soft Output Viterbi Algorithm (SOVA)” decoding for double-binary Circular Recursive Systematic Convolutional (CRSC) turbo codes is presented. The bi-directional SOVA is considered in view of its better performance and implementation complexity trade-off. The basic SOVA has been described for binary turbo code. We have extended it for double binary case, which is useful for high data rate healthcare applications using real time streaming data. Necessary changes in basic message passing equations for double-binary case have been introduced. Coding gain can be used to increase the robustness and immunity to interference. Decoding of CRSC codes requires a prologue decoder, prior to the actual trellis decoding, to estimate the initial state. Efficient determination of circulation state through prologue decoding has helped in achieving impressive error performance for CRSC codes. The issues related to digital implementation of turbo encoder/decoder and their effects on error performance have also been discussed. Adequate simulation results have been included.

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D. Bera, T. Chakravarty and S. Chakrabarti, "Reliable Wireless Communication for Medical Devices Using Turbo Convolution Code," International Journal of Communications, Network and System Sciences, Vol. 3 No. 8, 2010, pp. 703-710. doi: 10.4236/ijcns.2010.38094.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] C. Berrou, A. Glavieux and P. Thitimajshima, “Near Shannon Limit Error-Control Coding and Decoding: Turbo Codes,” Proceedings of IEEE International Conference on Communications, Geneva, 23-26 May 1993, pp. 1064- 1070.
[2] C. Berrou and M. Jezequel, “Non-Binary Convolutional Codes for Turbo Coding,” Electronics Letters, Vol. 35, No. 1, 1999, pp. 39-40.
[3] C. Douillard and C. Berrou, “Turbo Codes With Rate- m/(m + 1) Constituent Convolutional Codes,” IEEE Tra- nsactions on Communications, Vol. 53, No. 10, 2005, pp. 1630-1638.
[4] C. Berrou, C. Douillard and M. Jezequel, “Multiple Para- llel Concatenation of Circular Recursive Systematic Con- volutional (CRSC) Codes,” Annals of Telecommunica- tions, Vol. 54, No. 3-4, 1999, pp. 166-172.
[5] Digital Video Broadcasting, “Interaction Channel for Satellite Distribution Systems,” Guidelines for the User of EN 301 790, Version 1.3.1, 2003, pp. 23-27.
[6] B. Vucetic and J. Yuan “Turbo Codes: Principles and Applications,” Kluwer Academic Publishers, Boston, 2000.
[7] L. Bhal, J. Cocke, F. Jelinck and J. Raviv, “Optimal Decoding of Linear Codes for Minimizing Symbol Error Rate,” IEEE Transactions on Information Theory, Vol. 20, No. 2, 1974, pp. 284-287.
[8] J. A. Erfanian, S. Pasupathy and G. Gulak, “Reduced Complexity Symbol Detectors with Parallel Structures for ISI Channels,” IEEE Transactions on Communications, Vol. 42, No. 234, 1994, pp. 1661-1671.
[9] W. Koch and A. Baier, “Optimum and Sub-Optimum De- tection of Coded Data Disturbed by Time-Varying Inter- symbol Interference,” Proceedings of IEEE Global Tele- communications Conference, San Diego, Vol. 3, 2-5 Dec- ember 1990, pp. 1679-1684.
[10] P. Robertson, P. Hoher and E. Villebrun. “A Comparison of Optimal and Sub-Optimal MAP Decoding Algorithms Operating in the Log Domain,” Proceedings of IEEE International Conference on Communications, Seattle, 18- 22 June 1995, pp. 1009-1013.
[11] G. Battail, “Ponderation des Symbols Decodes par l’Al- gorithme de Viterbi,” Annals of Telecommunications, Vol. 42, No. 1-2, 1987, pp. 31-38.
[12] J. Hagenauer and P. Hoeher, “A Viterbi Algorithm with Soft-Decision Outputs and its Applications,” Proceedings of IEEE Global Telecommunications Conference, Dallas, 27-30 November 1989, pp. 1680-1686.
[13] C. Berrou, P. Adde, E. Angui and S. Faudeil, “A Low Complexity Soft-Output Viterbi Decoder Architecture,” Proceedings of IEEE International Conference on Com- munications, Geneva, Vol. 2, 23-26 May 1993, pp. 737- 740.
[14] J. B. Anderson and S. M. Hladik, “Tailbiting MAP De- coders,” IEEE Journal on Selected Areas in Communi- cations, Vol. 16, No. 2, 1998, pp. 297-302.
[15] D. Gianchristofaro and A. Bartolazzi, “Novel DVB-RCS Standard Turbo Code: Details and Performances of a Decoding Algorithm,” Proceedings of 7th International Workshop on Digital Signal Processing Techniques for Space Communications, Sesimbra, 1-3 October 2001.
[16] D. Bera and J. Sen, “SOVA Based Decoding of Double- Binary Turbo Convolutional Code,” Proceedings of 1st IEEE International Conference on Wireless Communi- cation, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology, Aalborg, 17-20 May 2009, pp. 757-761.
[17] D. Bera, “Design of Duo-Binary CRSC Turbo Convolution Code,” Proceedings of 4th IEEE International Conference on Computers and Devices for Communication, Kolkata, 14-16 December 2009, pp. 40-43.
[19] G. Masera, M. Mazza, G. Piccinini, F. Viglione and M. Zamboni, “Architectural Strategies for Low-Power VLSI Turbo Decoders,” IEEE Transactions on Very Large Scale Integration Systems, Vol. 10, No. 3, 2002, pp. 279-285.
[20] Y. Saouter, “Decoding M-Binary Turbo Codes by the Dual Method,” Proceedings of IEEE Information Theory Workshop, Paris, 31 March-4 April 2003, pp. 74-77.

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