Diep N. Nguyen
Skip Abstract Section
Abstract
We explore the use of cooperative multi-input multi-output (MIMO) communications to prolong the lifetime of a wireless sensor network (WSN). Single-antenna sensor nodes are clustered into virtual antenna arrays that can act as virtual MIMO (VMIMO) nodes. We design a distributed cooperative clustering protocol (CCP), which exploits VMIMO's diversity gain by optimally selecting the cooperating nodes (CNs) within each cluster and balancing their energy consumption. The problem of optimal CN selection at the transmit and receive clusters is formulated as a nonlinear binary program. Aiming at minimizing the imbalance in the residual energy at various nodes, we decompose this problem into two subproblems: finding the optimal number of CNs (ONC) in a cluster and the CN assignment problem. For the ONC problem, we first analyze the energy efficiency of two widely used VMIMO methods: distributed Space Time Block Code (DSTBC) and distributed Vertical-Bell Laboratories-Layered-Space-Time (DVBLAST). Our analysis provides an upper bound on the optimal number of CN nodes, which greatly reduces the computational complexity of the ONC problem. The second subproblem is addressed by assigning CNs based on the residual battery energy. To make CCP scalable to large WSNs, we propose a multihop energy-balanced routing mechanism for clustered WSNs (C-EBR) with a novel cost metric. Finally, we derive sufficient conditions on the intra- and intercluster ranges, under which CCP guarantees connectivity of the intercluster topology. Extensive simulations show that the proposed approach dramatically improves the network lifetime.
- M. Abramowitz and I. A. E. Stegun. 1972. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Dover Books on Mathematics, New York. Google Scholar
Digital Library
- A. Aksu and O. Ercetin. 2008. Reliable multi-hop routing with cooperative transmissions in energy-constrained networks. IEEE Trans. Wirel. Communi. 7, 8, 2861--2865. Google ScholarDigital Library
- A. Awad, T. Frunzke, and F. Dressler. 2007. Adaptive distance estimation and localization in WSN using RSSI measures. In Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools. 471--478. Google ScholarDigital Library
- W. N. Bailey. 1935. Appell's hypergeometric functions of two variables. In Generalised Hypergeometric Series. Vol. 32, Chap. 9, Cambridge University Press.Google Scholar
- S. Basagni. 1999. Distributed clustering for ad hoc networks. In Proceedings of the International Symposium on Parallel Architectures, Algorithms, and Networks. Google ScholarDigital Library
- D. Bertsimas and R. Weismantel. 2005. Optimization Over Integers. Dynamic Ideas, Charlestown, MA.Google Scholar
- D. M. Blough and P. Santi. 2002. Investigating upper bounds on network lifetime extension for cell-based energy conservation techniques in stationary ad hoc networks. In Proceedings of the ACM/IEEE International Conference on Mobile Computing and Networking (MOBICOM). 183--192. Google ScholarDigital Library
- L. H. Brandenburg and A. D. Wyner. 1974. Capacity of the Gaussian channel with memory: The multivariate case. ATT Tech. 53, 5, 745--778.Google Scholar
- J.-H. Chang and L. Tassiulas. 2004. Maximum lifetime routing in wireless sensor networks. IEEE/ACM Trans. Netw. 12, 609--619. Google ScholarDigital Library
- W. Chen, Y. Yuan, C. Xu, K. Liu, and Z. Yang. 2005. Virtual MIMO protocol based on clustering for wireless sensor network. In Proceedings of the 10th IEEE Symposium on Computers and Communications. Google ScholarDigital Library
- H. Chernoff. 1952. A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations. Ann. Math. Stat. 23, 4, 493--507.Google ScholarCross Ref
- S. Cui, A. J. Goldsmith, and A. Bahai. 2004. Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks. IEEE J. Select. Areas in Commun. 22, 6, 1089--1098. Google ScholarDigital Library
- M. Dohler, E. Lefranc, and H. Aghvami. 2002a. Space time block codes for virtual antenna arrays. In Proceedings of the PIMRC Conference (Lisbon, Portugal).Google Scholar
- M. Dohler, E. Lefranc, and H. Aghvami. 2002b. Virtual antenna arrays for future wireless mobile communication systems. In Proceedings of the ICT Conference (Beijing, China).Google Scholar
- J. Elson, L. Girod, and D. Estrin. 2002. Fine-grained network time synchronization using reference broadcasts. In Proceedings of the 5th Symposium on Operating Systems Design and Implementation. 147--163. Google ScholarDigital Library
- G. J. Foschini. 1996. Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas. Bell Labs Tech. J. 1, 2, 41--59.Google ScholarCross Ref
- G. J. Foschini and M. J. Gans. 1998. On limits of wireless communications in a fading environment when using multiple antennas. Wirel. Perso. Commun. 6, 311--335. Google ScholarDigital Library
- Q. Gao, Y. Zuo, J. Zhang, and X.-H. Peng. 2010. Improving energy efficiency in a wireless sensor network by combining cooperative MIMO with data aggregation. IEEE Trans. Vehic. Tech. 59, 8, 3956--3965.Google ScholarCross Ref
- D. Gong, M. Zhao, and Y. Yang. 2010. A multi-channel cooperative MIMO MAC protocol for wireless sensor networks. In Proceedings of the IEEE 7th International Conference on Mobile Adhoc and Sensor Systems (MASS). 11--20.Google Scholar
- P. Gupta and P. R. Kumar. 1998. Critical power for asymptotic connectivity in wireless networks. In Stochastic Analysis, Control, Optimization and Applications: A Volume in Honor of W.H. Fleming.Google Scholar
- W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan. 2000. Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8. Washington, DC. Google ScholarDigital Library
- W. Jaafar, W. Ajib, and D. Haccoun. 2010. On the performance of distributed-stbc in multi-hop wireless relay networks. In Proceedings of the European Wireless Conference. 223--230.Google Scholar
- G. Jakllari, S. V. Krishnamurthy, M. Faloutsos, P. V. Krishnamurthy, and O. Ercetin. 2006. A framework for distributed spatio-temporal communications in mobile ad hoc networks. In Proceedings of the IEEE INFOCOM Conference.Google Scholar
- S. Jayaweera. 2006. Virtual MIMO-based cooperative communication for energy-constrained wireless sensor networks. IEEE Trans. Wirel. Commun. 5, 5, 984--989. Google ScholarDigital Library
- S. Jayaweera. 2007. V-BLAST-based virtual MIMO for distributed wireless sensor networks. IEEE Trans. Commun. 55, 10, 1867--1872.Google ScholarCross Ref
- JEN JN5139 module datasheet, UK, http://www.jennic.com/support/datasheets/jn5139.Google Scholar
- J. Laneman and G. Wornell. 2003. Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks. IEEE Trans. Info. Theory 49, 10, 2415--2425. Google ScholarDigital Library
- E. G. Larsson, P. Stoica, E. Lindskog, and J. Li. 2002. Space-time block coding for frequency-selective channels. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). Vol. 3, 2405--2408. Google ScholarDigital Library
- X. Li, M. Chen, and W. Liu. 2005. Application of STBC-encoded cooperative transmissions in wireless sensor networks. IEEE Sig. Proc. Lett. 12, 2, 134--137.Google ScholarCross Ref
- Z. Li, and X.-G. Xia. 2008. An alamouti coded OFDM transmission for cooperative systems robust to both timing errors and frequency offsets. IEEE Trans. Wire. Commun. 7, 5, 1839--1844. Google ScholarDigital Library
- E. Lindskog and A. Paulraj. 2000. A transmit diversity scheme for channels with intersymbol interference. In Proceedings of the IEEE ICC Conference. Vol. 1, 307--311.Google Scholar
- Y. Mei, Y. Hua, A. Swami, and B. Daneshrad. 2005. Combating synchronization errors in cooperative relays. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). Vol. 3, 369--372.Google Scholar
- Mesquite Software Inc., http://www.mesquite.com.Google Scholar
- R. Narasimhan. 2003. Spatial multiplexing with transmit antenna and constellation selection for correlated MIMO fading channels. IEEE Trans. Signal Process. 51, 11, 2829--2838. Google ScholarDigital Library
- Q. Qu, L. B. Milstein, and D. R. Vaman. 2010. Cooperative and constrained MIMO communications in wireless ad hoc/sensor networks. IEEE Trans. Wire. Commun. 9, 10, 3120--3129. Google ScholarDigital Library
- P. Rong and M. Pedram. 2006. An analytical model for predicting the remaining battery capacity of lithium-ion batteries. IEEE Trans. VLSI Syst. 14, 5, 441--451. Google ScholarDigital Library
- J. Salz. 1985. Digital transmission over cross-coupled linear channels. ATT Tech. J. 64, 6, 1147--1159.Google ScholarCross Ref
- A. Scaglione, D. L. Goeckel, and J. N. Laneman. 2007. Cooperative communications in mobile ad-hoc networks: Rethinking the link abstraction. In Distributed Antenna Systems: Open Architecture for Future Wireless Communications. 87--116.Google Scholar
- H. Shin, and J. H. Lee. 2002. Exact symbol error probability of orthogonal space-time block codes. In Proceedings of the IEEE GLOBECOM Conference.Google Scholar
- O.-S. Shin, A. Chan, H. Kung, and V. Tarokh. 2007. Design of an OFDM cooperative space-time diversity system. IEEE Trans. Vehic. Tech. 56, 4, 2203--2215.Google ScholarCross Ref
- T. Shu and M. Krunz. 2010. Coverage time optimization for clustered wireless sensor networks: A power-balancing approach. IEEE/ACM Trans. Netw. 18, 1, 202--215. Google ScholarDigital Library
- M. Z. Siam, M. Krunz, and O. Younis. 2009. Energy-efficient clustering/routing for cooperative MIMO operation in sensor networks. In Proceedings of the IEEE INFOCOM Conference.Google Scholar
- M. Stemm and R. Katz. 1997. Measuring and reducing energy consumption of network interfaces in hand-held devices. IEICE Trans. Commun.Google Scholar
- V. Tarokh, H. Jafarkhani, and A. R. Calderbank. 1999. Space-time block codes from orthogonal designs. IEEE Trans. Info. Theory 45, 5, 1456--1467. Google ScholarDigital Library
- S. Wei, D. Goeckel, and M. Valenti. 2006. Asynchronous cooperative diversity. IEEE Trans. Wirel. Commun. 5, 6, 1547--1557. Google ScholarDigital Library
- F. Ye, G. Zhong, J. Cheng, S. Lu, and L. Zhang. 2003. PEAS: A robust energy conserving protocol for long-lived sensor networks. In Proceedings of the 23rd International Conference on Distributed Computing Systems. 28--37. Google ScholarDigital Library
- O. Younis and S. Fahmy. 2004. Heed: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. Mobile Comput. 3, 4, 366--379. Google ScholarDigital Library
- O. Younis, M. Krunz, and S. Ramasubramanian. 2006. Node clustering in wireless sensor networks: Recent developments and deployment challenges. IEEE Netw. Mag. 20, 20--25. Google ScholarDigital Library
- Y. Yuan, M. Chen, and T. Kwon. 2006a. A novel cluster-based cooperative MIMO scheme for multi-hop wireless sensor networks. EURASIP J. Wirel. Commun. Netw. 2. Google ScholarDigital Library
- Y. Yuan, Z. He, and M. Chen. 2006b. Virtual MIMO-based cross-layer design for wireless sensor networks. IEEE Trans. Vehic. Tech. 55, 3, 856--864.Google ScholarCross Ref
- L. Zhang and L. J. Cimini. 2008. Power-efficient relay selection in cooperative networks using decentralized distributed space-time block coding. EURASIP J. Adv. Sig. Process. Google ScholarDigital Library
- X. Zhang and K. G. Shin. 2010. DAC: Distributed asynchronous cooperation for wireless relay networks. In Proceedings of the IEEE INFOCOM Conference. Google ScholarDigital Library
- Q. Zhao, L. Tong, and D. Counsil. 2007. Energy-aware adaptive routing for large-scale ad hoc networks: Protocol and performance analysis. IEEE Trans. Mobile Comput. 6, 9, 1048--1059. Google ScholarDigital Library
- Y. Zhuang, J. Pan, and G. Wu. 2009. Energy-optimal grid-based clustering in wireless microsensor networks. In Proceedings of the IEEE ICDCS Workshop on Wireless Ad hoc and Sensor Networking (WWASN). Google ScholarDigital Library
- Y. Zhuang, J. Pan, and L. Cai. 2010. Minimizing energy consumption with probabilistic distance models in wireless sensor networks. In Proceedings of the IEEE INFOCOM Conference. Google ScholarDigital Library
- ZIG ZIGBEE, http://www.caba.org/standard/zigbee.html.Google Scholar
Index Terms
- A Cooperative MIMO Framework for Wireless Sensor Networks
Recommendations
Energy-aware routing algorithm for wireless sensor networks
Display Omitted A new energy aware routing algorithm has been proposed for cluster based wireless sensor networks.It achieves O(1) message complexity per sensor node and O(n) time complexity for a WSN having n sensor nodes.It efficiently forms the ...
An energy efficient clustering method for wireless sensor networks
EHAC'07: Proceedings of the 6th WSEAS International Conference on Electronics, Hardware, Wireless and Optical CommunicationsWireless sensor networks have many sensor nodes with a limited energy in a limited area. One of key issues in wireless sensor networks is to prolong the network lifetime. In this paper, we propose a scheme to construct an energy-efficient cluster ...
TTS: a two-tiered scheduling mechanism for energy conservation in wireless sensor networks
In this paper, we present a two-tiered scheduling approach for effective energy conservation in wireless sensor networks. The effectiveness of this mechanism relies on dynamically updated two-tiered scheduling architecture. We aim to prolong network ...
Comments