Cover
Vol. 7 No. 2 (2011)

Published: December 31, 2011

Pages: 130-137

Original Article

Energy-Efficiency of Dual-Switched Branch Diversity Receiver in Wireless Sensor Networks

Ghaida A. AL-Suhail 1
1Department of Computer Engineering College of Engineering, University of Basrah Basrah, Iraq
History
  • Received: October 31, 2011
  • Available Online: December 31, 2011
DOI

https://doi.org/10.37917/ijeee.7.2.8

Abstract

In this paper, we develop an analytical energy efficiency model using dual switched branch diversity receiver in wireless sensor networks in fading environments. To adapt energy efficiency of sensor node to channel variations, the optimal packet length at the data link layer is considered. Within this model, the energy efficiency can be effectively improved for switch-and-stay combiner (SSC) receiver with optimal switching threshold. Moreover, to improve energy efficiency, we use error control of Bose-Chaudhuri-Hochquengh (BCH) coding for SSC-BPSK receiver node compared to one of non-diversity NCFSK receiver of sensor node. The results show that the BCH code for channel coding can improve the energy efficiency significantly for long link distance and various values of high energy consumptions over Rayleigh fading channel.

Keywords

References

  1. M. Vieira, C.N. Coelho, D.C. da Silva, “Survey on Wireless Sensor Network Devices,” IEEE Conf. Emerging Technol. Factory Autom. , pp. 537-544, Sep. 2003.
  2. P. Lettieri, C. Fragouli, and M.B. Srivastava, “Low Power Error Control for Wireless Links,” ACM/IEEE Int. Conf. Mobile Comput. Netw., pp. 139-150, 1997.
  3. E. Shih, S. H. Cho, F. S. Lee, B. H. Calhoum, and A. Chandrakasan, “Design Considerations for Energy-Efficient Radios in Wireless Microsensor Networks,” J. VLSI Signal Process, vol. 37, no. 1, pp. 7794, May 2004.
  4. M. Holland, Optimization Physical Layer Parameters for Wireless Sensor Networks, MSc. Thesis in Electrical and Computer Engineering, University of Rochester, New York, 2007.
  5. M. Goel and N. R. Shanbhag, “Low Power Channel Coding Via Dynamic Reconfiguration,” Proceedings of ICASSP, Phoenix, AZ, pp. 1893-1896, March 1999.
  6. http: www.embeddedcomputing.com
  7. S. S. Chakraborty, M. Liinaharja and K. Ruttik, “Diversity and packet combining in Rayleigh fading channels,” IEE Proc. Commun, vol. 152, no.3, pp. 353-356, June 2005.
  8. X. Cai and G. B. Giannakis, “Performance Analysis of Combined Transmit Selection Diversity and Receive Generalized Selection Combining in Rayleigh Fading Channels,” IEEE Trans on Wireless Commun. , 2004.
  9. E. Cianca, A. D. Luise, M Ruggieri, and R. Prasad, “Channel-Adaptive Techniques in Wireless Communications: An Overview.” Wireless Commun. Mob. Compu ., 2:799-813, 2002.
  10. B. Holter and G. E. Oien, “Performance Analysis of a Rate-Adaptive Dual-Branch Switched Diversity System,” IEEE on Trans. on Commun., vol. 56, no. 12, pp. 1998-2001, Dec. 2008.
  11. M. K. Simon and M.-S. Alouini, Digital Communication over Fading Channels , 2 nd edition, J. Wiley, New Jersey, 2005.
  12. Y. Sankarasubramaniam, I. F. Akyildiz and S. W. McLaughlin, “Energy Efficiency based Packet Size Optimization in Wireless Sensor Networks”, Proc. of the 1 st IEEE International Workshop on Sensor Network Protocols and Applications , May 2003.
  13. H. Karvonen, C. Pomalaza-Raez and M.Hamalainen, “Cross-Layer Energy Efficiency of FEC Coding in UWB Sensor Networks ,” Proc. of IEEE Inter. Conf. on Ultra-Wideband , pp. 337-362, Sept. 24-27 2006.
  14. J. Haapola, Z. Shelby, C. Pomalaza-Raez, and P. Mahonen, “Crosslayer Energy Analysis of Multip-hop Wireless Sensor Networks ,” Networks , Feb 2005.
  15. G. Balakrishnan, M. Yang, Y. Jiang, and Y. Kim, “Performance Analysis of Error Control Codes for Wireless Sensor Networks,” Int. Conf. Inf. Technol. , pp. 876-879, 2007.
  16. S. L. Howard, C. Schlegel, and K. Iniewski, “Error Control Coding in Low-power Wireless Sensor Networks: When is ECC energyefficient?,” EURASIP J. Wireless Commun. Netw. , no. 2, pp. 1-14, 2006.
  17. S. Chauhan, R. Bose, and M. Balakrishnan, “ A Framework of EnergyConsumption-Based Design Space Exploration for Wireless Sensor Nodes,” IEEE Trans. On Computer-Aided Design of Integrated Circuit and system , vol. 38, no. 7, July 2009.
  18. J. Abouei, K.N. Plataniotis, and S. Pasupathy, ,”Green Modulation in dense Wireless Sensor Networks,” IEEE Inter. Conference on Acoustic, Speech and Signal Processing (ICASSP’09) , Sept. 2009.
  19. S. K. Jayaweera, “Energy Analysis of MIMO Techniques in WSNs, Proc. Annu. Conf. on Info. Sciences and Systems (CISS), USA, Princeton, March 2004.
  20. S. Hussain, A. Azim, and J. H. Park, “Energy Efficient Virtual MIMO Communication for Wireless Sensor Networks,” Springer, Telecommun Syst (2009) : 42:139-149, June 2009.
  21. N. Shastry and R.S. Adve, “A Theoretical Analysis of Cooperative Diversity in Wireless Sensor Networks,” GlobCom05 , 2005.
  22. S. Wang and J. Nie, “Energy Efficiency Optimization of Cooperative Communication in Wireless Sensor Networks,” EURASIP J. on Wireless Comm. And Networking, vol. 2010.
  23. I. Joe, “Optimal Packet Length with Energy Efficiency for Wireless Sensor Networks,” IEEE Inter. Symp. Circ. And Sys. ISCAS2005, 2320 May 2005.