Abstract
We consider a remote estimation problem with an energy-harvesting sensor and a remote estimator. The sensor harvests energy from its environment (say, for example, through a solar cell) and uses this energy for the purpose of communicating with the estimator. Due to the randomness of energy available for communication, we need to find a communication scheduling strategy for the sensor. The estimator relies on messages communicated by the sensor to produce real-time estimates of the sensor's observations. We consider the problem of finding a communication scheduling strategy for the sensor and an estimation strategy for the estimator that jointly minimize an expected sum of communication and distortion costs over a finite time horizon. We find a dynamic programming characterization of optimal strategies. Under some symmetry assumptions on source statistics and the distortion metric, we show that an optimal communication strategy is a threshold based one and that the optimal estimate is always the most recently received sensor observation.
Original language | English (US) |
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Article number | 6426984 |
Pages (from-to) | 843-848 |
Number of pages | 6 |
Journal | Proceedings of the IEEE Conference on Decision and Control |
DOIs | |
State | Published - 2012 |
Event | 51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States Duration: Dec 10 2012 → Dec 13 2012 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization