Performance analysis of wireless sensor network with virtual MIMO

In this work, ray based simulation approach has been used for estimating the performance of WSN with MIMO and SISO techniques. The ray based simulation should produce more accurate results than model based simulation approach because it is more close to real life environment. In addition to simulation, Markov model based analytical approach has also been adopted. The transition probabilities among various states of the Markov model has been evaluated using the data produced by the ray trace simulator. It is also giving better performance as compared to Rayleigh fading channel based Markov models approach. LEACH clustering protocol has been used with a slight modification in terms of selecting secondary cluster head. Alamouti space-time code has been used with V-MIMO and significant improvement in the overall life time has been observed as compared to SISO WSN.

[1]  Andrea J. Goldsmith,et al.  Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks , 2004, IEEE Journal on Selected Areas in Communications.

[2]  Mohamed Ibnkahla,et al.  Wireless sensor networks: Applications and challenges , 2007, 2007 9th International Symposium on Signal Processing and Its Applications.

[3]  Saleem A. Kassam,et al.  Finite-state Markov model for Rayleigh fading channels , 1999, IEEE Trans. Commun..

[4]  Zongkai Yang,et al.  An Energy-Efficient Cooperative MIMO Transmission Scheme for Wireless Sensor Networks , 2006, 2006 International Conference on Wireless Communications, Networking and Mobile Computing.

[5]  Jinsang Kim,et al.  Energy efficient cooperative MIMO in wireless sensor network , 2008, 2008 International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

[6]  Rohit U. Nabar,et al.  Introduction to Space-Time Wireless Communications , 2003 .

[7]  Sudharman K. Jayaweera Energy Analysis of MIMO Techniques in Wireless Sensor Networks , 2004 .

[8]  Siavash M. Alamouti,et al.  A simple transmit diversity technique for wireless communications , 1998, IEEE J. Sel. Areas Commun..

[9]  Andrea J. Goldsmith,et al.  Energy-constrained modulation optimization , 2005, IEEE Transactions on Wireless Communications.

[10]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[11]  Sudharman K. Jayaweera,et al.  Virtual MIMO-based cooperative communication for energy-constrained wireless sensor networks , 2006, IEEE Transactions on Wireless Communications.

[12]  Hamid Aghvami,et al.  Space-time block codes for virtual antenna arrays , 2002, The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[13]  Sudharman K. Jayaweera,et al.  An energy-efficient virtual MIMO architecture based on V-BLAST processing for distributed wireless sensor networks , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..