Dynamic Resource Optimization for Decentralized Signal Estimation in Energy Harvesting Wireless Sensor Networks

We study decentralized estimation of time-varying signals at a fusion center (FC), when energy harvesting sensors transmit sampled data over rate-constrained links. We propose a dynamic strategy based on stochastic optimization for selecting radio parameters, sampling set, and harvested energy at ea...

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Bibliographic Details
Published inICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 4454 - 4458
Main Authors Lorenzo, Paolo Di, Battiloro, Claudio, Banelli, Paolo, Barbarossa, Sergio
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2019
Subjects
energy harvesting
probabilistic quantization
Signal recovery
stochastic optimization
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Summary:We study decentralized estimation of time-varying signals at a fusion center (FC), when energy harvesting sensors transmit sampled data over rate-constrained links. We propose a dynamic strategy based on stochastic optimization for selecting radio parameters, sampling set, and harvested energy at each node, with the aim of estimating a time-varying signal with guaranteed performance while ensuring stability of the batteries around a prescribed operating level. Numerical results validate the proposed approach for dynamic signal estimation under communication and energy constraints.
ISSN:2379-190X
DOI:10.1109/ICASSP.2019.8683440