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Energy-efficient adaptive transmission power control for wireless body area networks

Energy-efficient adaptive transmission power control for wireless body area networks

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An important constraint in wireless body area network (WBAN) is to maximise the energy-efficiency of wearable devices due to their limited size and light weight. Two experimental scenarios; ‘right wrist to right hip’ and ‘chest to right hip’ with body posture of walking are considered. It is analyzed through extensive real-time data sets that due to large temporal variations in the wireless channel, a constant transmission power and a typical conventional transmission power control (TPC) methods are not suitable choices for WBAN. To overcome these problems a novel energy-efficient adaptive power control (APC) algorithm is proposed that adaptively adjusts transmission power (TP) level based on the feedback from base station. The main advantages of the proposed algorithm are saving more energy with acceptable packet loss ratio (PLR) and lower complexity in implementation of desired tradeoff between energy savings and link reliability. We adapt, optimise and theoretically analyse the required parameters to enhance the system performance. The proposed algorithm sequentially achieves significant higher energy savings of 40.9%, which is demonstrated by Monte Carlo simulations in MATLAB. However, the only limitation of proposed algorithm is a slightly higher PLR in comparison to conventional TPC such as Gao's and Xiao's methods.

References

    1. 1)
      • 1. IEEE Std. 802.15.6: ‘IEEE standard for local and metropolitan area networks — part 15.6: WBAN’. IEEE, 3 Park Avenue, New York, USA, 2012.
    2. 2)
    3. 3)
      • 3. Chipcon: ‘CC2420: 2.4 GHz IEEE 802.15.4/ZigBee-ready RF transceiver’. Available at http://www.chipcon.com.
    4. 4)
      • 4. Kim, S., Eom, D.-S.: ‘Link-state-estimation-based transmission power control in WBANs’, 2014.
    5. 5)
    6. 6)
      • 6. Di Bari, R., Alomainy, A., Hao, Y., et al: ‘Cooperative and low-power wireless sensor network for efficient body-centric communications in healthcare applications’. Proc. Third Int. Conf. of (MobiHealth), France, November 2012.
    7. 7)
    8. 8)
    9. 9)
      • 9. Kubisch, M., Karl, H.: ‘Distributed algorithms for transmission power control in wireless sensor networks’. Proc. IEEE WCNC, New Orleans, Louisiana, USA, March 2003.
    10. 10)
      • 10. Son, D., Krishnamachari, B.: ‘Experimental study of the effects of transmission power control and blacklisting in wireless sensor networks’. Proc. IEEE SECON, Santa Clara, CA, USA, October 2004.
    11. 11)
      • 11. Lin, S., Zhang, J., Zhou, G.: ‘ATPC: adaptive transmission power control for wireless sensor networks’. Proc. Fourth ACM SenSys, Boulder, CO, USA, November 2006.
    12. 12)
      • 12. See, T.S.P., Ge, Y.: ‘Experimental correlation of path loss with system performance in WBAN for healthcare Applications’. Proc. 13th Int. Conf. on Healthcom, Columbia, MO, USA, June 2011.
    13. 13)
      • 13. Ge, Y., Kwan, J.W.: ‘Performance benchmarking for wireless body area networks at 2.4 GHz’. Proc. 22nd Int. Symp. on Personal, Indoor and Mobile Radio Communications, Toronto, CA, USA, September 2011.
    14. 14)
    15. 15)
      • 15. Moulton, B., Hanlen, L., Chen, J., et al: ‘BAN TPC using variable adaptive feedback periodicity’. IEEE, 2010.
    16. 16)
      • 16. Dhamdhere, A., Sivaraman, V., Mathur, V., et al: ‘Algorithms for transmission power control in biomedical wireless sensor networks’. IEEE Asia-Pacific Services Computing Conf., 2008.
    17. 17)
      • 17. Xiao, S., Sivaraman, V.: ‘Adapting radio transmit power in WBASNs’, 2006.
    18. 18)
    19. 19)
    20. 20)
      • 20. Kazemi, R., Vesilo, R.: ‘Inter-network interference mitigation in wireless body area networks using power control games’. Proc. 10th Int. Symp. Communications and Information Technologies (ISCIT), Tokyo, Japan, October 2010.
    21. 21)
    22. 22)
      • 22. Hassan, A., Li, Y.: ‘Battery-friendly packet transmission strategies for wireless capsule endoscopy’. IFMBE, Springer Proc., February 2014.
    23. 23)
    24. 24)
    25. 25)
    26. 26)
    27. 27)
      • 27. NICTA. Available at http://www.nicta.com.au/.
    28. 28)
      • 28. Kannan, Srinivasan, , Maria, A. Kaz, , Saatvik, Agarwal: ‘The β-factor: improving bimodal wireless networks’. Technical Report, SING-07-01, Computer Systems Laboratory Stanford University Stanford, CA 94131, 2007.
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