Channel Estimated Cooperative MIMO in Wireless Sensor Network

Abstract Energy efficient data transfer is the key factor for the design of energy efficient wireless sensor network (WSN). In this paper, an energy efficient cooperative MIMO (C-MIMO) technique is proposed in the WSN where fixed constellation size is considered in transmitting both the local and long-haul communication. A selection criterion is used based on the channel conditions where a selected number of sensors in a cluster is used to form a multiple input multiple output (MIMO) structure wirelessly connected with multiple antennas of a data gathering node (DGN). The selected approach is tested on the correlated data scenario. Experimental results show that the selected C-MIMO structure outperforms the unselected C-MIMO in terms of total energy consumption and they show energy efficient performance over existing one when they are compared with SISO structure. Energy models are evaluated for this scenario while energy consumption and efficiency are compared for different combination of cluster sizes and selected number of sensors. Comparisons are shown for different fixed number of constellation sizes. The effect of correlation coefficient and intersensor distance are analyzed. Later, a delay analysis is shown considering optimal constellation size.

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

[2]  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.

[3]  Elif Uysal-Biyikoglu,et al.  Energy-efficient packet transmission over a wireless link , 2002, TNET.

[4]  Ana García Armada,et al.  An Energy-Efficient Adaptive Modulation Suitable for Wireless Sensor Networks with SER and Throughput Constraints , 2007, EURASIP J. Wirel. Commun. Netw..

[5]  A. Robert Calderbank,et al.  Space-Time block codes from orthogonal designs , 1999, IEEE Trans. Inf. Theory.

[6]  Andrea J. Goldsmith,et al.  Modulation optimization under energy constraints , 2003, IEEE International Conference on Communications, 2003. ICC '03..

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

[8]  Mahdi Lotfinezhad,et al.  Effect of partially correlated data on clustering in wireless sensor networks , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[9]  Kang Lee IEEE 1451: A standard in support of smart transducer networking , 2000, Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference [Cat. No. 00CH37066].

[10]  Yan Meng,et al.  Algorithm/Architecture Co-exploration for Designing Energy Efficient Wireless Channel Estimator , 2005, J. Low Power Electron..

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

[12]  Viktor K. Prasanna,et al.  Energy-latency tradeoffs for data gathering in wireless sensor networks , 2004, IEEE INFOCOM 2004.

[13]  Ashutosh Sabharwal,et al.  Delay-bounded packet scheduling of bursty traffic over wireless channels , 2004, IEEE Transactions on Information Theory.

[14]  Yi Gai,et al.  Energy Efficiency of Cooperative MIMO with Data Aggregation in Wireless Sensor Networks , 2007, 2007 IEEE Wireless Communications and Networking Conference.

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

[16]  Jinsang Kim,et al.  Energy Efficient Cooperative Technique for IEEE 1451 Based Wireless Sensor Network , 2008, 2008 IEEE Wireless Communications and Networking Conference.

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

[18]  Thomas H. Lee,et al.  The Design of CMOS Radio-Frequency Integrated Circuits: RF CIRCUITS THROUGH THE AGES , 2003 .

[19]  Georgios B. Giannakis,et al.  Energy-efficient scheduling for wireless sensor networks , 2005, IEEE Transactions on Communications.

[20]  J.E. Mazo,et al.  Digital communications , 1985, Proceedings of the IEEE.

[21]  Niraj K. Jha,et al.  High-level software energy macro-modeling , 2001, Proceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232).

[22]  Ashutosh Sabharwal,et al.  Delay-constrained scheduling: power efficiency, filter design, and bounds , 2004, IEEE INFOCOM 2004.