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A Comprehensive Study of Channel Estimation for WBAN-based Healthcare Systems: Feasibility of Using Multiband UWB

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Abstract

Wireless personal area network (WPAN) is an emerging in wireless technology for short range indoor and outdoor communication applications. A more specific category of WPAN is the wireless body area network (WBAN) used for health monitoring. On the other hand, multiband orthogonal frequency division multiplexing (MB-OFDM) ultra-wideband (UWB) comes with a number of desirable features at the physical layer for wireless communications, for example, very high data rate. One big challenge in adoption of multiband UWB in WBAN is the fact that channel estimation becomes difficult under the constraint of extremely low transmission power. Moreover, the heterogeneous environment of WBAN causes a dense multipath wireless channel. Therefore, effective channel estimation is required in the receiver of WBAN-based healthcare system that uses multiband UWB. In this paper, we first outline the MB-OFDM UWB system. Then, we present an overview of channel estimation techniques proposed/investigated for multiband UWB communications with emphasis on their strengths and weaknesses. Useful suggestions are given to overcome the weaknesses so that these methods can be particularly useful for WBAN channels. Also, we analyze the comparative performances of the techniques using computer simulation in order to find the energy-efficient channel estimation methods for WBAN-based healthcare systems.

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References

  1. Jung, S., Lauterbach, C., Strasser, M., and Weber, W., Enabling technologies for disappearing electronics in smart textiles. In Proceedings of IEEE ISSCC03. San Francisco, CA, USA, February, 2003.

  2. Stoica, L., Rabbachin, A., Repo, H. O., Tiuraniemi, T. S., and Oppermann, I., An ultrawideband system architecture for tag based wireless sensor networks. IEEE Trans. Veh. Technol. 54:1632–1645, 2005.

    Article  Google Scholar 

  3. Zasowski, T., Althaus, F., and Wittneben, A., Temporal cognitive UWB medium access in the presence of multiple strong signal interferers. In: Proceedings of the 14th IST mobile and wireless communications summit. Dresden, Germany, June, 2005.

  4. Somayazulu, V. S., Foerster, J. R., and Roy, S., Design challenges for very high data rate UWB systems. In: Proceedings of the 36th Asilomar conference on signals, systems and computer. Hillsboro, OR, USA, November, 2002.

  5. Porcino, D., and Hirt, W., Ultra-wideband radio technology: potential and challenges ahead. IEEE Commun. Mag. 41:66–74, 2003.

    Article  Google Scholar 

  6. Jianli, P., and Jain, R., Medical applications of Ultra-wideband (UWB). http://www.cse.wustl.edu/~jain/cse574-08/ftp/uwb/index.html, Date visited: 10 Aug, 2010.

  7. Molisch, A., Foerster, J., and Pendergrass, M., Channel models for ultra-wideband personal area networks. IEEE Wireless Communications Magazine, pp. 14–21, December 2003.

  8. Molisch, A., Foerster, J., and Pendergrass, M., Standard ECMA-368: high rate ultra wideband PHY and MAC standard, 2nd Edition. ECMA International, December 2008.

  9. Bo, Y., and Yang, L. Wireless body area network for healthcare: a feasibility study. http://www.ieee.org/documents/Yu_Final_Published_Paper_March2009.pdf, Date visited: 10 Aug, 2010.

  10. Takizawa, K., Aoyagi, T., and Kohno, R., Channel modeling and performance evaluation of UWB-based wireless body area networks. IEEE International Conference of Communications (ICC), Dresden, Germany, 2009.

    Google Scholar 

  11. Li, Y., Minn, H., and Rajatheva, R. M. A. P., Synchroization, Channel Estimation and Equalization in MB-OFDM Systems. IEEE Trans. Wireless Commun. 7(11):4341–4352, 2008.

    Article  Google Scholar 

  12. Munier, F., and Eriksson, T., Time-frequency channel estimation for MB-OFDM UWB systems. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Helsinki, Finland, 2006.

    Google Scholar 

  13. Kay, S. M. Fundamentals of statistical signal processing. Prentice Hall International, 1993.

  14. Yang, X., Zhu, X., and Wang, Y., Analysis of DFT-based channel estimation algorithm for UWB-OFDM system. IET International Conference on Wireless, Mobile and Multimedia Networks, Mumbai, India, 2008.

    Google Scholar 

  15. Fan, X., Leng, B., Zhang, Z., and Bi, G., An improved channel estimation algorithm for OFDM UWB. In Proceedings of IEEE WCNC, Vol. 1, September 2005.

  16. Wang, J., Shen, K., and Jiang, L., Algorithms of Channel Estimation and Tracking in MB-OFDM UWB Systems. WRI World Congr. Comput. Sci. Inf. Eng. CSIE 1:465–469, 2009.

    Google Scholar 

  17. Fan, X., Leng, B., Zhang, Z., and Bi, G., Modified UWB channel estimation. The 2nd International Conference on Mobile Technology, Applications and Systems, Guangzhou, China, 2005.

  18. Li, X., and Qiu, H., Study on channel estimation for UWB MB-OFDM. International Conference on Communication Technology (ICCT), Guilin, 2006.

    Google Scholar 

  19. Peng, K., Peng, X., and Chin, F., A low complexity adaptive channel estimation scheme for MB-OFDM system. IEEE International Conference on Ultra-wideband (ICUWB), Germany, 2008.

    Google Scholar 

  20. Tasi, Y., Wang, C., and Li, X., Adaptive channel estimation for MB-OFDM systems in multi-access interfering environments. IEEE Vehicular Technology Conference (VTC), Singapore, 2008.

    Google Scholar 

  21. Li, C., Zheng, G., and Zhu, Y., A study of channel estimation in multi-band OFDM UWB systems. Auswireless International Conference on Wireless Broadband and Ultra Wideband Communications, Sydney, Australia, 2006.

    Google Scholar 

  22. Xu, J., Lu, X., Bian, Y., and Zou, D. Ultra-wideband MB-OFDM channel estimation with pilots. The 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), Dalian, China, October 2008.

  23. Raffallo, T., Matti, H., and Jari, I., Channel estimation algorithms comparison for Multiband-OFDM. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Helsinki, Finland, 2006.

    Google Scholar 

  24. Keijo, P., and Koi, V., Iterative interpolation method for Multiband-OFDM channel estimation. IEEE International Conference on Ultra-wideband (ICUWB), Singapore, 2007.

    Google Scholar 

  25. Hadaschik, N., Zakia, I., Ascheid, G., and Meyr, H., Joint narrowband interference detection and channel estimation for wideband OFDM. In: Proceedings of the European Wireless Conference, April 2007.

  26. Niels, H., and Gerd, A., Deriving a joint interference detection and channel estimation for WB-OFDM from EM-MAP Theory. In: Proceedings of IEEE International Conference of Communications (ICC), Beijing, China, May 2008.

  27. Islam, S. M. R., and Kwak, K. S., Winner-Hopf interpolation aided Kalman filter-based channel estimation for MB-OFDM UWB systems in time varying dispersive fading channel. The 12th International Conference on Advanced Communication Technology (ICACT), Phoenix Park, Korea, 2010.

    Google Scholar 

  28. Lowe, D., and Huang, X., Ultra-wideband MB-OFDM channel estimation with complementary codes. IEEE International Symposium on Communications and Information Technologies (ISCIT), Bangkok, Thailand, 2006.

    Google Scholar 

  29. Sadough, S. M. S., Mahieddine, M., Ichir, P. D., and Emmanuel J., Wavelet-based semiblind channel estimation for ultrawideband OFDM systems. IEEE Trans. Veh. Technol. 58(3), March 2009.

  30. Sadough, S. M. S., Mahieddine, M., Ichir, P. D., and Emmanuel, J., Ultra-wideband OFDM channel estimation through a wavelet based EM-MAP Algorithm. Eur. Trans. Telecommun. 19:761–771, 2008.

    Article  Google Scholar 

  31. Xu, H., Chong, C., Guvenc, I., Watanabe, F., and Yang, L., High-resolution TOA estimation with multi-band OFDM signals. In: Proceedings of IEEE International Conference of Communications (ICC), Beijing, China, May 2008.

  32. Minn, H., Bhargava, V., and Letaief, K., A Robust Timing and Frequency Synchronization for OFDM Systems. IEEE Trans. Wireless Commun. 2(4):822–839, 2003.

    Article  Google Scholar 

  33. Minn, H., Bhargava, V., and Letaief, K., A combined timing and frequency synchronization and channel estimation for OFDM. IEEE Trans. Wireless Commun. 54(3):416–422, 2006.

    Google Scholar 

  34. Yao, Y., Dong, X., and Tin, N., A new joint timing and channel estimation method for block transmission UWB systems. IEEE International Conference on Communications (ICC), Dresden, Germany, 2009.

    Google Scholar 

  35. Julier, S. J., and Uhlmann J. K., Unscented filtering and nonlinear estimation. IEEE Review 92(3), March 2004.

  36. Xu, B., and Bi, G., Channel estimation using complementary sequence pairs for UWB/OFDM systems. IEE Electron. Lett. 40(9):1196–1197, 2004.

    Article  Google Scholar 

  37. Harada, H., Marco, H., and Ryuji, K., Channel estimation for wavelet packet based UWB transmissions. IEEE 9th International Symposium on Spread Spectrum Techniques and Applications, Amazon, Brazil, August 2006.

  38. Berrou, C., Glavieux, A., and Thitimajshima, P., Near Shannon limit error-correcting coding and decoding: turbo-codes. (1). In: Proceedings of IEEE International Conference on Communications (ICC '93), vol. 2, Geneva, Switzerland, pp. 1064–1070, May 1993.

  39. Bahl, L. R., Cocke, J., Jelinek, F., and Raviv, J., Optimal decoding of linear codes for minimizing symbol error rate. IEEE Trans. Inf. Theory IT-20(2):284–287, 1974.

    Article  MathSciNet  Google Scholar 

  40. Li, Y., Molisch, A. F., and Zhang, J., Practical approaches to channel estimation and interference suppression for OFDM based UWB communications. IEEE 6th CAS Symposium on Emerging Technologies: Mobile and Wireless Communications, Shanghai, China, 2004.

  41. Shin, S., Yang, Q., and Kwak, K. S., Performance analysis of MB-OFDM system using SVD Aimed LMMSE channel estimation. IEEE International Conference on Ultra-wideband (ICUWB), Singapore, 2007.

    Google Scholar 

  42. Ray, B., Venkataraghavan, P. K., and Sriram, B., Equalization for multiband OFDM based UWB systems. IEEE Vehicular Technology Conference (VTC), Dublin, Ireland, 2007.

    Google Scholar 

  43. Sherratt, R. S., Cadenas, O., and Yang, R., A practical low cost architecture for MB-OFDM equalizer (ECMA-368). 11th Annual IEEE International Symposium of Consumer Electronics (ISCE), Texas, USA, June 2007.

  44. Karl, H., and Wiling, A., Protocols and architectures for wireless sensor networks. John Wiley & Sons, Ltd, 2005.

  45. Siriwongpairat, W. P., and Liu, K. J. R., Ultra-wideband communications systems: multiband OFDM approach. John Wiley & Sons, Inc., New Jersey, 2008.

    Google Scholar 

  46. Bajwa, W. U., Haupt, J., Raz, G., and Nowak, R., Compressed channel sensing. 42nd Annual Conference on Information Sciences and Systems (CISS), Princeton, NJ, March 2008.

  47. Babadi, B., Kalouptsidis, N., and Tarokh, V., SPARLS: a low complexity recursive L 1 -regularized least squares algorithm. Submitted for Publications, (http://arxiv1.library.cornell.edu/PS_cache/arxiv/pdf/0901/0901.0734v1.pdf, date visited: 26 Feb, 2010), Draft January 2009.

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Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2010-0018116).

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Authors and Affiliations

  1. Graduate School of Information and Telecommunications, Inha University, 6-143, 253, Yong-hyun-dong, Nam-Gu, 402-751, Incheon, Souh Korea

    S. M. Riazul Islam

  2. Graduate School of Information and Telecommunications, Inha University, 6-142, UWB-ITRC, 253, Yong-hyun-dong, Nam-Gu, 402-751, Incheon, Souh Korea

    Kyung Sup Kwak

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  1. S. M. Riazul Islam
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Correspondence to S. M. Riazul Islam.

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Additional Notes

1. BAN Network Controller (BNC): A typical BAN may consists of few devices (called BAN nodes) and scalable to hundred nodes. They are controlled by BNC.

2. Cyclic Prefix (CP): Cyclic prefix refers to the prefixing of OFDM symbol with a repetition of the end. It serves two purposes. First, is the guard interval that eliminates ISI. The other is the repetition of the end. It allows DFT operations on information bits.

3. Zero Padding (ZP): Zero padding has the same purpose as that of CP but consists of extending a signal with zeros. The advantage of the use ZP over CP is the easier design of non-linear power amplifier. The ECMA-368 standard of MB-OFDM UWB uses ZP instead of CP.

4. Carrier Frequency Offset (CFO): This refers to the difference in carrier frequency at transmitter (TX) and receiver (RX). The input carrier frequency at the receiver can vary due to Doppler Effect, caused by relative motion between TX and RX, multipath components and other sources of CFO.

5. Pilot: Pilot is a known signal transmitted over a communications system for control, equalization and synchronization or reference purposes.

6. Preamble: It is a pilot signal used during synchronization.

7. Fine Timing Offset: This refers to the drifts in symbol timing at the receiver (RX) after initial symbol synchronization between symbol timing in TX and that in RX.

8. Power Delay Profile (PDP): This provides the intensity of a signal received through a multipath channel as a function of time delay. The time delay is the difference in travel time between multipath arrivals.

9. Narrowband Interference (NBI): In the study of UWB system narrowband (NB) implies bandwidth under consideration is “sufficiently” narrow compared to the UWB bandwidth. A wideband (WB) system, by its nature, interferes with the existing NB services in the same frequency band and in turn, the NB signals act as interferers to WB system. This interference is termed NBI.

10. Current channel and predicted channel estimate: The Kalman filter produces estimates of the true values of channel measurements and their associated calculated values by predicting a value, estimating the uncertainty of the predicted value, and computing a weighted average of the predicted value and the measured value. Estimates of the true values of channel measurements are termed current channel estimates. In contrast, the estimates of associated calculated values are called predicted channel estimates.

11. Notational Concerns:

• Subscripts/superscripts p, H, F, T, * stand for pilot, Hermitian transpose, feedback, transpose and complex conjugate respectively. Whereas, over bar/hat –, ^ denote for mathematical mean and statistical estimate respectively.

• Small letters h, s, r are used for time domain vectors/matrices, whose frequency domain vectors are donated by corresponding capital letters H, S, R respectively.

• Operators E{.} represents the expected value of the term within the bracket.

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Islam, S.M.R., Kwak, K.S. A Comprehensive Study of Channel Estimation for WBAN-based Healthcare Systems: Feasibility of Using Multiband UWB. J Med Syst 36, 1553–1567 (2012). https://doi.org/10.1007/s10916-010-9617-6

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