Energy Efficiency of Collaborative Communication with Imperfect Frequency Synchronization in Wireless Sensor Networks

  • Husnain Naqvi
  • Stevan Berber
  • Zoran Salcic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6059)


Collaborative communication produces significant (N 2 where N is number of nodes used for collaboration) power gain and overcomes the effect of fading. With imperfect frequency synchronization significant but slightly less than N 2 power can be achieved. As the N increases more power gain can be achieved at the expense of more circuit power. In this paper an energy consumption model for collaborative communication system with imperfect frequency synchronization is proposed. The model to calculate the energy consumed by the sensor network for local communication and communication with base station is presented. Energy efficiency model for collaborative communication for the off-the shell products (CC2420 and AT86RF212) are presented. It is also shown that significant energy can be saved using collaborative communication as compared to traditional SISO (Single input single output) for products. The break-even distance where the energy consumed by SISO and collaborative communication is also calculated. From results it is revealed that collaborative communication using 5 nodes produces efficient energy saving.


Sensor Network Collaborative Communication Bit Error Rate Rayleigh Fading Energy Consumption Frequency Synchronization energy Efficiency 


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  1. 1.
    Estrin, D., Girod, L., Pottie, G., Srivastava, M.: Instrumenting the world with wireless sensor networks. In: Proc. IEEE Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), vol. 4, pp. 2033–2036 (2033)Google Scholar
  2. 2.
    Kahn, J.M., Katz, R.H., Pister, K.S.J.: Next century challenges: mobile networking for smart dust. In: MobiCom 1999: Proc. 5th ACM/IEEE Intl. Conf. on Mobile Computing and Networking, pp. 271–2781 (1999)Google Scholar
  3. 3.
    Barriac, G., Mudumbai, R., Madhow, U.: Distributed beamforming for information transfer in sensor networks. In: Proc. 3rd International Symposium on Information Processing in Sensor Networks (IPSN 2004), April 26–27, pp. 81–88 (2004)Google Scholar
  4. 4.
    Han, Z., Poor, H.V.: Lifetime improvement in wireless sensor networks via collaborative beamforming and cooperative transmission. Microwaves, Antennas & Propagation, IET 1, 1103–1110 (2007)CrossRefGoogle Scholar
  5. 5.
    Mudumbai, R., Barriac, G., Madhow, U.: On the feasibility of distributed beamforming in wireless networks. IEEE Trans. Wireless Commun. 6(5), 1754–1763 (2007)CrossRefGoogle Scholar
  6. 6.
    Naqvi, H., Berber, S.M., Salcic, Z.: Collaborative Communication in Sensor Networks. Technical report No. 672, University of Auckland Engineering Library (2009)Google Scholar
  7. 7.
    Naqvi, H., Berber, S.M., Salcic, Z.: Performance Analysis of Collaborative Communication with imperfect Frequency Synchronization and AWGN in Wireless Sensor Networks. In: Proceedings of The 2009 International Conference on Future Generation Communication and Networking, Jeju Island, Korea (December 2009)Google Scholar
  8. 8.
    Schurgers, C., Aberthorne, O., Srivastava, M.B.: Modulation scaling for energy aware communication systems. In: Proc. Int. Symp. Low Power Electronics Design, August 2001, pp. 96–99 (2001)Google Scholar
  9. 9.
    Min, R., Chandrakasan, A.: A framework for energy-scalable communication in high-density wireless networks. In: Proc. Int. Symp. Low Power Electronics Design, August 2002, pp. 36–41 (2002)Google Scholar
  10. 10.
    Cui, S., Goldsmith, A.J., Bahai, A.: Modulation optimization under energy constraints. In: Proc. ICC 2003, AK, May 2003, pp. 2805–2811 (2003),
  11. 11.
    Cui, S., Goldsmith, A.J., Bahai, A.: Energy-Efficiency of MIMO and Cooperative MIMO Techniques in Sensor Networks. IEEE Journal on Selected Areas In Communications 22(6), 1089–1098 (2004)CrossRefGoogle Scholar
  12. 12.
    Simić, L., Berber, S., Sowerby, K.W.: Energy-Efficiency of Cooperative Diversity Techniques in Wireless Sensor Networks. In: The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2007 (2007)Google Scholar
  13. 13.
    Sklar, B.: Rayleigh fading channels in mobile digital communication systems.I. Characterization. IEEE Communications Magazine 35(7), 90–100 (1997)CrossRefGoogle Scholar
  14. 14.
    Goldsmith, A.: Wireless communications, pp. 31–42. Cambridge University Press, Cambridge (2005)Google Scholar
  15. 15.
  16. 16.
  17. 17.
    Cheng, J., Beaulieu, N.C.: Accurate DS-CDMA bit-error probability calculation in Rayleigh fading. IEEE Trans. on Wireless Commun. 1(1), 3–15 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Husnain Naqvi
    • 1
  • Stevan Berber
    • 1
  • Zoran Salcic
    • 1
  1. 1.Department of Electrical and Computer EngineeringThe University of AucklandNew Zealand

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