Energy-efficient design of VMIMO for WSN applications

Abstract

Wireless sensor networks (WSNs) have been paid more attention in recent years. However, energy efficiency is still a troublesome issue in real WSN applications. In this paper, we studied the performance of a virtual multiple-input multiple-output (VMIMO)-based communications architecture for WSN applications. By analyzing the bit error rate (BER) of each cooperative branch, we presented the closed-form expressions for optimal transmitting power (TP) scheme in K×1 VMIMO cluster-based system. Then, the impact of the number of cooperating nodes on energy efficiency with energy-per-useful-bit (EPUB) metric was studied. Performance enhancement of the strategy with optimal TP assignment was verified by extensive simulations under different scenes. A thorough explanation of optimally choosing the number of cooperating nodes was also delivered by the aid of simulation verifications.

Key words： energy efficiency; virtual multiple-input multiple-output (VMIMO); wireless sensor networks (WSNs)

References

1 Akyildiz I F, Su W, Sankarasubramaniam Y, Cayirci E. Wireless sensor networks: A survey. Computer Networks, 2002, 38(4): 393–422

2 Ren F Y, Huang H N, Lin C. Wireless sensor networks. Journal of Software, 2003, 14(7): 1282–1291 (in Chinese)

3 Ma Z C, Sun Y N, Mei T. Survey on wireless sensors network. Journal of China Institute of Communications, 2004, 25(4): 114–124 (in Chinese)

4 Zhao B H, Li J, Zhan W, Qu Y G. MIMO-based energy-efficient wireless sensor networks. Acta Electronica Sinica, 2006, 34(8): 1415–1419 (in Chinese)

5 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, 2004, 22(6): 1089–1098

6 Li X, Chen M, Liu W. Application of STBC-encoded cooperative transmissions in wireless sensor networks. IEEE Signal Processing Letters, 2005, 12(2): 134–137

7 Cover T M, El Gamal A A. Capacity theorems for the relay channel. IEEE Transactions on Information Theory, 1979, 25(5): 572–584

8 Dohler M, Gkelias A, Hamid Aghvami A. Capacity of distributed PHY-layer sensor networks. IEEE Transactions on Vehicular Technology, 2006, 55(2): 622–639

9 Jagannathan S, Aghajan H, Goldsmith A. The effect of time synchronization errors on the performance of cooperative MISO system. In: Proceedings of IEEE Global Telecommunications Conference. 2004, 102–107

10 Yuan Y, He Z H, Chen M. Virtual MIMO-based cross-layer design for wireless sensor networks. IEEE Transactions on Vehicular Technology, 2006, 55(3): 856–864

11 Laneman J N, Wornell G W. Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks. IEEE Transactions on Information Theory, 2003, 49(10): 2415–2425

12 Yang Z, Høst-Madsen A. Routing and power allocation in asynchronous Gaussian multiple-relay channels. EURASIP Journal on Wireless Communications and Networking, 2006, 2006: 056914

13 Li F, Lippman A, Wu K. Minimum energy cooperative path routing in wireless networks: An integer programming formulation. In: Proceedings of the 63rd IEEE Vehicular Technology Conference VTC06. 2006, <month>1</month>–<day>6</day>

14 Khandani A E, Abounadi J, Modiano E, Zheng L. Cooperative routing in static wireless networks. IEEE Transactions on Communications, 2007, 55(11): 2185–2192

15 Ibrahim A S, Han Z, Liu K J. Distributed energy-efficient cooperative routing in wireless networks. IEEE Transactions on Wireless Communications, 2008, 7(10): 3930–3941

16 Lakshmanan S, Sivakumar R. Diversity routing for multi-hop wireless networks with cooperative transmissions. In: Proceedings of the 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks. 2009, 610–618x003b2;

17 Rossi M, Tapparello C, Tomasin S. On optimal cooperator selection policies for multi-hop ad hoc networks. IEEE Transactions on Wireless Communications, 2011, 10(2): 506–518

18 Jayaweera S K. Virtual MIMO-based cooperative communication for energy-constrained wireless sensor networks. IEEE Transactions on Wireless Communications, 2006, 5(5): 984–989

19 Cui S, Goldsmith A J, Bahai A. Energy-constrained modulation optimization. IEEE Transactions on Wireless Communications, 2005, 4(5): 2349–2360

20 Chung S T, Goldsmith A J. Degrees of freedom in adaptive modulation: A unified view. IEEE Transactions on Communications, 2001, 49(9): 1561–1571

21 Boyd S, Vandenberghe L. Convex Optimization. Cambridge: Cambridge University Press, 2004

22 Li X. Energy efficient wireless sensor networks with transmission diversity. IEE Electronics Letters, 2003, 39(24): 1753–1755

23 Ammer J, Rabacy J. The energy-per-useful-bit metric for evaluating and optimizing sensor network physical layers. In: Proceedings of the 3rd Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks. 2006, 2: 695–700

24 Kan B Q, Cai L, Zhu H S, Xu Y J. Accurate energy model for WSN node and its optimal design. Journal of Systems Engineering and Electronics, 2008, 19(3): 427–433