Abstract
This paper considers a wireless network composed of a pair of sensors powered by energy harvesting devices (EHDs), which transmit data to a receiver over a shared wireless channel. At any given time, based on the energy levels of the two rechargeable batteries of the sensors, a central controller (CC) decides on the amount of energy to be drawn from the two batteries and used for transmission. The problem considered is the maximization of the long-term average reward associated with data transmission, by optimizing the transmission strategy of the two nodes, in the case of a collision channel model and both i.i.d. and correlated energy arrivals. In addition, contrary to the traditional assumption that the amount of energy available to the sensors can be easily estimated, we derive the optimal policy in the cases where the state of charge (SOC) may not be perfectly known by the central controller, analyzing the performance degradation caused by this imperfect knowledge of the SOC. For this second scenario, supposing that the CC is only aware that each SOC is 'LOW' or 'HIGH,' we show that the impact of imperfect knowledge decreases with the two battery capacities and is negligible in most cases of practical interest.
Original language | English (US) |
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Article number | 7296672 |
Pages (from-to) | 1393-1405 |
Number of pages | 13 |
Journal | IEEE Transactions on Wireless Communications |
Volume | 15 |
Issue number | 2 |
DOIs | |
State | Published - Feb 2016 |
Externally published | Yes |
Keywords
- Energy harvesting
- Markov decision processes
- renewable energy sources
- wireless sensor networks
ASJC Scopus subject areas
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics