Energy Scheduling for Optical Channels with Energy Harvesting Devices

Vaneet Aggarwal, Zhe Wang, Xiaodong Wang, Muhammad Ismail Muhammad

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Optical communication systems (with visible light communication as an example) have emerged as a promising candidate for supporting high throughput requirements. Such high data rates can be achieved in a sustainable manner when energy harvesting devices are adopted for the optical transmitters. However, the existing research lacks a thorough investigation on the maximum achievable capacity for optical networks under dynamic energy conditions. This is especially true when photon counter detectors are implemented at the receiver side, and hence, optical Poisson channels are considered. To address this limitation, we develop in this paper optimal energy scheduling algorithms for optical Poisson channels with energy harvesting devices. The objective is to maximize the channel sum-rate, assuming that the side information of energy harvesting states for {K} time slots is known a priori, and the battery capacity and the maximum energy consumption in each time slot are bounded. The problem is formulated as a convex optimization program with {{\mathcal{ O}}(K)} constraints, making it hard to solve using a general convex solver since the computational complexity of a generic convex solver is exponential in the number of constraints. This paper proposes an efficient energy scheduling algorithm that has a reduced computational complexity of {{\mathcal {O}}(K^{2})}. The proposed algorithm is also proven to be optimal. The developed energy schedule is piece-wise constant, which changes when the battery overflows or depletes. Numerical results depict significant improvement of the optimal strategy over benchmark strategies.

Original languageEnglish
Pages (from-to)154-162
Number of pages9
JournalIEEE Transactions on Green Communications and Networking
Volume2
Issue number1
DOIs
Publication statusPublished - 1 Mar 2018

Fingerprint

Energy harvesting
Scheduling
Scheduling algorithms
Computational complexity
Convex optimization
Optical communication
Fiber optic networks
Communication systems
Energy utilization
Photons
Throughput
Detectors

Keywords

  • convex optimization
  • energy harvesting
  • Energy schedule
  • KKT conditions
  • Poisson channel
  • visible light communications (VLC)

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Renewable Energy, Sustainability and the Environment

Cite this

Energy Scheduling for Optical Channels with Energy Harvesting Devices. / Aggarwal, Vaneet; Wang, Zhe; Wang, Xiaodong; Muhammad, Muhammad Ismail.

In: IEEE Transactions on Green Communications and Networking, Vol. 2, No. 1, 01.03.2018, p. 154-162.

Research output: Contribution to journalArticle

@article{bacc2c934b2c489b8520138aa102a2b6,
title = "Energy Scheduling for Optical Channels with Energy Harvesting Devices",
abstract = "Optical communication systems (with visible light communication as an example) have emerged as a promising candidate for supporting high throughput requirements. Such high data rates can be achieved in a sustainable manner when energy harvesting devices are adopted for the optical transmitters. However, the existing research lacks a thorough investigation on the maximum achievable capacity for optical networks under dynamic energy conditions. This is especially true when photon counter detectors are implemented at the receiver side, and hence, optical Poisson channels are considered. To address this limitation, we develop in this paper optimal energy scheduling algorithms for optical Poisson channels with energy harvesting devices. The objective is to maximize the channel sum-rate, assuming that the side information of energy harvesting states for {K} time slots is known a priori, and the battery capacity and the maximum energy consumption in each time slot are bounded. The problem is formulated as a convex optimization program with {{\mathcal{ O}}(K)} constraints, making it hard to solve using a general convex solver since the computational complexity of a generic convex solver is exponential in the number of constraints. This paper proposes an efficient energy scheduling algorithm that has a reduced computational complexity of {{\mathcal {O}}(K^{2})}. The proposed algorithm is also proven to be optimal. The developed energy schedule is piece-wise constant, which changes when the battery overflows or depletes. Numerical results depict significant improvement of the optimal strategy over benchmark strategies.",
keywords = "convex optimization, energy harvesting, Energy schedule, KKT conditions, Poisson channel, visible light communications (VLC)",
author = "Vaneet Aggarwal and Zhe Wang and Xiaodong Wang and Muhammad, {Muhammad Ismail}",
year = "2018",
month = "3",
day = "1",
doi = "10.1109/TGCN.2017.2771381",
language = "English",
volume = "2",
pages = "154--162",
journal = "IEEE Transactions on Green Communications and Networking",
issn = "2473-2400",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "1",

}

TY - JOUR

T1 - Energy Scheduling for Optical Channels with Energy Harvesting Devices

AU - Aggarwal, Vaneet

AU - Wang, Zhe

AU - Wang, Xiaodong

AU - Muhammad, Muhammad Ismail

PY - 2018/3/1

Y1 - 2018/3/1

N2 - Optical communication systems (with visible light communication as an example) have emerged as a promising candidate for supporting high throughput requirements. Such high data rates can be achieved in a sustainable manner when energy harvesting devices are adopted for the optical transmitters. However, the existing research lacks a thorough investigation on the maximum achievable capacity for optical networks under dynamic energy conditions. This is especially true when photon counter detectors are implemented at the receiver side, and hence, optical Poisson channels are considered. To address this limitation, we develop in this paper optimal energy scheduling algorithms for optical Poisson channels with energy harvesting devices. The objective is to maximize the channel sum-rate, assuming that the side information of energy harvesting states for {K} time slots is known a priori, and the battery capacity and the maximum energy consumption in each time slot are bounded. The problem is formulated as a convex optimization program with {{\mathcal{ O}}(K)} constraints, making it hard to solve using a general convex solver since the computational complexity of a generic convex solver is exponential in the number of constraints. This paper proposes an efficient energy scheduling algorithm that has a reduced computational complexity of {{\mathcal {O}}(K^{2})}. The proposed algorithm is also proven to be optimal. The developed energy schedule is piece-wise constant, which changes when the battery overflows or depletes. Numerical results depict significant improvement of the optimal strategy over benchmark strategies.

AB - Optical communication systems (with visible light communication as an example) have emerged as a promising candidate for supporting high throughput requirements. Such high data rates can be achieved in a sustainable manner when energy harvesting devices are adopted for the optical transmitters. However, the existing research lacks a thorough investigation on the maximum achievable capacity for optical networks under dynamic energy conditions. This is especially true when photon counter detectors are implemented at the receiver side, and hence, optical Poisson channels are considered. To address this limitation, we develop in this paper optimal energy scheduling algorithms for optical Poisson channels with energy harvesting devices. The objective is to maximize the channel sum-rate, assuming that the side information of energy harvesting states for {K} time slots is known a priori, and the battery capacity and the maximum energy consumption in each time slot are bounded. The problem is formulated as a convex optimization program with {{\mathcal{ O}}(K)} constraints, making it hard to solve using a general convex solver since the computational complexity of a generic convex solver is exponential in the number of constraints. This paper proposes an efficient energy scheduling algorithm that has a reduced computational complexity of {{\mathcal {O}}(K^{2})}. The proposed algorithm is also proven to be optimal. The developed energy schedule is piece-wise constant, which changes when the battery overflows or depletes. Numerical results depict significant improvement of the optimal strategy over benchmark strategies.

KW - convex optimization

KW - energy harvesting

KW - Energy schedule

KW - KKT conditions

KW - Poisson channel

KW - visible light communications (VLC)

UR - http://www.scopus.com/inward/record.url?scp=85054050118&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85054050118&partnerID=8YFLogxK

U2 - 10.1109/TGCN.2017.2771381

DO - 10.1109/TGCN.2017.2771381

M3 - Article

AN - SCOPUS:85054050118

VL - 2

SP - 154

EP - 162

JO - IEEE Transactions on Green Communications and Networking

JF - IEEE Transactions on Green Communications and Networking

SN - 2473-2400

IS - 1

ER -