Abstract
In this letter, we propose an online power allocation (PA) method to maximize energy efficiency (EE) in energy harvesting systems with realistic battery constraints for two receivers. The optimization problem in this system configuration is challenging since it has a non-convex fractional form and the information of channel quality and the harvested energy can only be obtained causally in practice. To overcome these issues, we design time-average EE maximization through Lyapunov optimization techniques where the transmission power is computed with current battery information and channel fading. Moreover, based on random matrix theory, we present a simplified online EE algorithm. Numerical experiments verify that the proposed PA outperforms conventional online approaches with much reduced computational complexity.
| Original language | English |
|---|---|
| Article number | 8516396 |
| Pages (from-to) | 24-28 |
| Number of pages | 5 |
| Journal | IEEE Signal Processing Letters |
| Volume | 26 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2019 Jan |
Bibliographical note
Funding Information:Manuscript received July 30, 2018; revised October 1, 2018; accepted October 27, 2018. Date of publication November 12, 2018; date of current version November 19, 2018. This work was supported by the National Research Foundation through the Ministry of Science, ICT and Future Planning, South Korean Government, under Grant 2017R1A2B3012316. The associate editor coordinating the review of this manuscript and approving it for publication was Antonio García Marques. (Corresponding author: Inkyu Lee.) M. Ashraf and I. Lee are with the School of Electrical Engineering, Korea University, Seoul 02841, South Korea (e-mail:, mateenashraf@korea. ac.kr; [email protected]).
Publisher Copyright:
© 1994-2012 IEEE.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- Energy harvesting
- Lyapunov optimization
- online power allocation
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
- Applied Mathematics
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