Energy-Constrained Optimal Quantization for Wireless Sensor Networks
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Research Article Energy-Constrained Optimal Quantization for Wireless Sensor Networks Xiliang Luo1 and Georgios B. Giannakis2 1 Qualcomm
Inc., San Diego, CA 92121, USA of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA
2 Department
Correspondence should be addressed to Georgios B. Giannakis, [email protected] Received 28 May 2007; Revised 15 October 2007; Accepted 2 November 2007 Recommended by Huaiyu Dai As low power, low cost, and longevity of transceivers are major requirements in wireless sensor networks, optimizing their design under energy constraints is of paramount importance. To this end, we develop quantizers under strict energy constraints to effect optimal reconstruction at the fusion center. Propagation, modulation, as well as transmitter and receiver structures are jointly accounted for using a binary symmetric channel model. We first optimize quantization for reconstructing a single sensor’s measurement, and deriving the optimal number of quantization levels as well as the optimal energy allocation across bits. The constraints take into account not only the transmission energy but also the energy consumed by the transceiver’s circuitry. Furthermore, we consider multiple sensors collaborating to estimate a deterministic parameter in noise. Similarly, optimum energy allocation and optimum number of quantization bits are derived and tested with simulated examples. Finally, we study the effect of channel coding on the reconstruction performance under strict energy constraints and jointly optimize the number of quantization levels as well as the number of channel uses. Copyright © 2008 X. Luo and G. B. Giannakis. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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INTRODUCTION
Wireless sensor networks (WSN) are gaining increasing research interest for their emerging potential in both consumer and national security applications. Sensor networks are envisioned to be used for surveillance, identification, and tracking of targets. They can also serve as the first line of detection for various types of biological hazards such as toxic gas attacks. In civilian applications, WSN can be used to monitor the environment and measure quantities such as temperature and pollution levels. In most application scenarios, WSN nodes are powered by small batteries, which are practically nonrechargeable, either due to cost limitations or because they are deployed in hostile environments with high temperature, high pollution levels, or high nuclear radiation levels. These considerations motivate well energy-saving and energy-efficient WSN designs. One approach to prolong battery lifetime is the use of energy-harvesting radios as the ones in [1] with power dissipation levels below 100 μW. A lot of research has been carried out to devise energy efficient algorithms in each layer of WSN [2]. Optimal modulation with minimum en-
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