Abstract
This paper explores the usage of cooperative multiple input multiple output (MIMO) technique to minimize energy consumption used to establish communications among distant nodes in a wireless sensor network (WSN). As energy depletion is an outstanding problem in WSN research field, a number of techniques aim to preserve such resource, especially by means of savings during communication among sensor nodes. One such wide used technique is multi-hop communication to diminish the energy required by a single node to transmit a given message, providing a homogeneous consumption of the energy resources among the nodes in the network. However, it is not the case that multi-hop is always more efficient than single-hop, even that it may represent a great depletion of a single node’s energy. In this paper a cooperative MIMO transmission technique for WSN is presented, which is compared to single-hop and multi-hop transmission ones, highlighting its advantages in relation to both. Simulation results support the statement about the utility in applying the proposed technique for energy saving purposes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Business Week: 21 ideas for the 21st century, August 30, pp. 78–167 (1999)
Mini, R.A.F., Loureiro, A.A.F.: Energy in Wireless Sensor Networks. In: Garbinato, B., Miranda, H., Rodrigues, L. (eds.) Middleware for Network Eccentric and Mobile Applications, pp. 3–24. Springer (2009)
Goyal, D., Tripathy, M.R.: Routing Protocols in Wireless Sensor Networks: A Survey. In: Second International Conference on Advanced Computing & Communication Technologies, pp. 474–480 (2012)
Durresi, A., Paruchuri, V., Barolli, L., Raj, J.: QoS-energy aware broadcast for sensor networks. In: Proceedings of 8th ISPAN, p. 6 (2005)
Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A survey on sensor networks. IEEE Communications Magazine 40(8), 102–114 (2002)
Boyinbode, O., Le, H., Mbogho, A., Takizawa, M., Poliah, R.: A Survey on Clustering Algorithms for Wireless Sensor Networks. In: 13th International Conference on Network-Based Information Systems, pp. 358–364 (2010)
Chen, C., Ma, J., Yu, K.: Designing Energy-Efficient Wireless Sensor Networks with Mobile Sinks. In: Sensys 2006. ACM (2006)
Nakamura, E.F., Loureiro, A.A.F., Frery, A.C.: Information fusion for wireless sensor networks: Methods, models, and classifications. ACM Computing Surveys (CSUR) 39(3), Article 9, 1–55 (2007)
Hill, J., Culler, D.: A wireless embedded sensor architecture for system-level optimization, 12 p. Technical Report, UC Berkeley (2002)
Jayaweera, S.K.: Energy analysis of MIMO techniques in wireless sensor networks. In: 38th Annual Conf. on Information Science and Systems, Princeton, NJ, USA (2004)
Li, X., Chen, M., Liu, W.: Application of STBC-encoded cooperative transmissions in wireless sensor networks. IEEE Sig. Proc. Letters 12(2), 134–137 (2005)
Cui, S., Goldsmith, A.J., Bahai, A.: Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks. IEEE Journal on Select. Areas Communications 22(6), 1089–1098 (2004)
Del Galdo, G., Haardt, M., Schneider, C.: Geometry-based channel modeling in MIMO scenarios in comparison with channel sounder measurements. Advances in Radio Science - Kleinheubacher Berichte 2, 117–126 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
de Freitas, E.P., da Costa, J.P.C.L., de Almeida, A.L.F., Marinho, M. (2012). Applying MIMO Techniques to Minimize Energy Consumption for Long Distances Communications in Wireless Sensor Networks. In: Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networking. ruSMART NEW2AN 2012 2012. Lecture Notes in Computer Science, vol 7469. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32686-8_35
Download citation
DOI: https://doi.org/10.1007/978-3-642-32686-8_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32685-1
Online ISBN: 978-3-642-32686-8
eBook Packages: Computer ScienceComputer Science (R0)