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Energy-Constrained Optimal Quantization for Wireless Sensor Networks

Abstract

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.

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Correspondence to Georgios B. Giannakis.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Luo, X., Giannakis, G.B. Energy-Constrained Optimal Quantization for Wireless Sensor Networks. EURASIP J. Adv. Signal Process. 2008, 462930 (2007). https://doi.org/10.1155/2008/462930

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Keywords

  • Wireless Sensor Network
  • Quantization Level
  • Fusion Center
  • Transmission Energy
  • Multiple Sensor
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