Energy efficient online power allocation for two users with energy harvesting

Mateen Ashraf; Jaehoon Jung; Hun Min Shin; Inkyu Lee

doi:10.1109/LSP.2018.2878947

Energy efficient online power allocation for two users with energy harvesting

Mateen Ashraf, Jaehoon Jung, Hun Min Shin, Inkyu Lee

School of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

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	https://doi.org/10.1109/LSP.2018.2878947
Publication status	Published - 2019 Jan

Keywords

Energy harvesting
Lyapunov optimization
online power allocation

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering
Applied Mathematics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/LSP.2018.2878947

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title = "Energy efficient online power allocation for two users with energy harvesting",

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.",

keywords = "Energy harvesting, Lyapunov optimization, online power allocation",

author = "Mateen Ashraf and Jaehoon Jung and Shin, {Hun Min} and Inkyu Lee",

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 Garc{\'i}a 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; inkyu@korea.ac.kr). Publisher Copyright: {\textcopyright} 1994-2012 IEEE.",

year = "2019",

month = jan,

doi = "10.1109/LSP.2018.2878947",

language = "English",

volume = "26",

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issn = "1070-9908",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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AU - Ashraf, Mateen

AU - Jung, Jaehoon

AU - Shin, Hun Min

AU - Lee, Inkyu

N1 - 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; inkyu@korea.ac.kr). Publisher Copyright: © 1994-2012 IEEE.

PY - 2019/1

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N2 - 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.

AB - 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.

KW - Energy harvesting

KW - Lyapunov optimization

KW - online power allocation

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ER -

Energy efficient online power allocation for two users with energy harvesting

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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