### Abstract

In this paper, we study the optimum estimation of a continuous-time random process by using discrete-time samples taken by a sensor powered by energy harvesting power sources. The system employs a best-effort sensing scheme to cope with the stochastic nature of the energy harvesting sources. The best-effort sensing scheme defines a set of equally-spaced candidate sensing instants, and the sensor performs sensing at a given candidate sensing instant if there is sufficient energy available, and remains silent otherwise. It is shown through asymptotic analysis that when the energy harvesting rate is strictly less than the energy consumption rate, there is a non-negligible percentage of silent symbols due to energy outage. For a given average energy harvesting rate, a larger sampling period means a smaller energy outage probability and/or more energy per sample, but a weaker temporal correlation between two adjacent samples. Such a tradeoff relationship is captured by developing a closed-form expression of the estimation MSE, which analytically identifies the interactions among the various system parameters, such as the ratio between the energy harvesting rate and energy consumption rate, the sampling period, and the energy allocation between sensing and transmission. It is shown through theoretical analysis that the optimum performance can be achieved by adjusting the sampling period and sampling energy such that the average energy harvesting rate is equal to the average consumption rate.

Original language | English (US) |
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Title of host publication | Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015 |

Publisher | Institute of Electrical and Electronics Engineers Inc. |

Pages | 1134-1138 |

Number of pages | 5 |

ISBN (Electronic) | 9781467377041 |

DOIs | |

State | Published - Sep 28 2015 |

Event | IEEE International Symposium on Information Theory, ISIT 2015 - Hong Kong, Hong Kong Duration: Jun 14 2015 → Jun 19 2015 |

### Publication series

Name | IEEE International Symposium on Information Theory - Proceedings |
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Volume | 2015-June |

ISSN (Print) | 2157-8095 |

### Other

Other | IEEE International Symposium on Information Theory, ISIT 2015 |
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Country | Hong Kong |

City | Hong Kong |

Period | 6/14/15 → 6/19/15 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Theoretical Computer Science
- Information Systems
- Modeling and Simulation
- Applied Mathematics

### Cite this

*Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015*(pp. 1134-1138). [7282632] (IEEE International Symposium on Information Theory - Proceedings; Vol. 2015-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2015.7282632

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*Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015.*, 7282632, IEEE International Symposium on Information Theory - Proceedings, vol. 2015-June, Institute of Electrical and Electronics Engineers Inc., pp. 1134-1138, IEEE International Symposium on Information Theory, ISIT 2015, Hong Kong, Hong Kong, 6/14/15. https://doi.org/10.1109/ISIT.2015.7282632

**Optimum sensing of a time-varying random event with energy harvesting power sources.** / Wu, Jingxian; Akingeneye, Israel; Yang, Jing.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Optimum sensing of a time-varying random event with energy harvesting power sources

AU - Wu, Jingxian

AU - Akingeneye, Israel

AU - Yang, Jing

PY - 2015/9/28

Y1 - 2015/9/28

N2 - In this paper, we study the optimum estimation of a continuous-time random process by using discrete-time samples taken by a sensor powered by energy harvesting power sources. The system employs a best-effort sensing scheme to cope with the stochastic nature of the energy harvesting sources. The best-effort sensing scheme defines a set of equally-spaced candidate sensing instants, and the sensor performs sensing at a given candidate sensing instant if there is sufficient energy available, and remains silent otherwise. It is shown through asymptotic analysis that when the energy harvesting rate is strictly less than the energy consumption rate, there is a non-negligible percentage of silent symbols due to energy outage. For a given average energy harvesting rate, a larger sampling period means a smaller energy outage probability and/or more energy per sample, but a weaker temporal correlation between two adjacent samples. Such a tradeoff relationship is captured by developing a closed-form expression of the estimation MSE, which analytically identifies the interactions among the various system parameters, such as the ratio between the energy harvesting rate and energy consumption rate, the sampling period, and the energy allocation between sensing and transmission. It is shown through theoretical analysis that the optimum performance can be achieved by adjusting the sampling period and sampling energy such that the average energy harvesting rate is equal to the average consumption rate.

AB - In this paper, we study the optimum estimation of a continuous-time random process by using discrete-time samples taken by a sensor powered by energy harvesting power sources. The system employs a best-effort sensing scheme to cope with the stochastic nature of the energy harvesting sources. The best-effort sensing scheme defines a set of equally-spaced candidate sensing instants, and the sensor performs sensing at a given candidate sensing instant if there is sufficient energy available, and remains silent otherwise. It is shown through asymptotic analysis that when the energy harvesting rate is strictly less than the energy consumption rate, there is a non-negligible percentage of silent symbols due to energy outage. For a given average energy harvesting rate, a larger sampling period means a smaller energy outage probability and/or more energy per sample, but a weaker temporal correlation between two adjacent samples. Such a tradeoff relationship is captured by developing a closed-form expression of the estimation MSE, which analytically identifies the interactions among the various system parameters, such as the ratio between the energy harvesting rate and energy consumption rate, the sampling period, and the energy allocation between sensing and transmission. It is shown through theoretical analysis that the optimum performance can be achieved by adjusting the sampling period and sampling energy such that the average energy harvesting rate is equal to the average consumption rate.

UR - http://www.scopus.com/inward/record.url?scp=84969776601&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84969776601&partnerID=8YFLogxK

U2 - 10.1109/ISIT.2015.7282632

DO - 10.1109/ISIT.2015.7282632

M3 - Conference contribution

AN - SCOPUS:84969776601

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 1134

EP - 1138

BT - Proceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -