The energy efficiency of intelligent reflecting surface (IRS) enabled internet of things (IoT) networks is studied in this letter. The energy efficiency is mathematically expressed, respectively, as the number of reflecting elements and the spectral efficiency of the network and is shown to scale in the logarithm of the reflecting elements number in the high regime of transmit power from source node. Furthermore, it is revealed that the energy efficiency scales linearly over the spectral efficiency in the high regime of transmit power, in contrast to conventional studies on energy and spectral efficiency trade-offs in the non-IRS wireless IoT networks. Numerical simulations are carried out to verify the derived results for the IRS enabled IoT networks.
Juan ZHAO
Nanjing University of Posts and Telecommunications
Wei-Ping ZHU
Nanjing University of Posts and Telecommunications,Concordia University
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Juan ZHAO, Wei-Ping ZHU, "Scaling Law of Energy Efficiency in Intelligent Reflecting Surface Enabled Internet of Things Networks" in IEICE TRANSACTIONS on Fundamentals,
vol. E105-A, no. 4, pp. 739-742, April 2022, doi: 10.1587/transfun.2021EAL2061.
Abstract: The energy efficiency of intelligent reflecting surface (IRS) enabled internet of things (IoT) networks is studied in this letter. The energy efficiency is mathematically expressed, respectively, as the number of reflecting elements and the spectral efficiency of the network and is shown to scale in the logarithm of the reflecting elements number in the high regime of transmit power from source node. Furthermore, it is revealed that the energy efficiency scales linearly over the spectral efficiency in the high regime of transmit power, in contrast to conventional studies on energy and spectral efficiency trade-offs in the non-IRS wireless IoT networks. Numerical simulations are carried out to verify the derived results for the IRS enabled IoT networks.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2021EAL2061/_p
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@ARTICLE{e105-a_4_739,
author={Juan ZHAO, Wei-Ping ZHU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Scaling Law of Energy Efficiency in Intelligent Reflecting Surface Enabled Internet of Things Networks},
year={2022},
volume={E105-A},
number={4},
pages={739-742},
abstract={The energy efficiency of intelligent reflecting surface (IRS) enabled internet of things (IoT) networks is studied in this letter. The energy efficiency is mathematically expressed, respectively, as the number of reflecting elements and the spectral efficiency of the network and is shown to scale in the logarithm of the reflecting elements number in the high regime of transmit power from source node. Furthermore, it is revealed that the energy efficiency scales linearly over the spectral efficiency in the high regime of transmit power, in contrast to conventional studies on energy and spectral efficiency trade-offs in the non-IRS wireless IoT networks. Numerical simulations are carried out to verify the derived results for the IRS enabled IoT networks.},
keywords={},
doi={10.1587/transfun.2021EAL2061},
ISSN={1745-1337},
month={April},}
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TY - JOUR
TI - Scaling Law of Energy Efficiency in Intelligent Reflecting Surface Enabled Internet of Things Networks
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 739
EP - 742
AU - Juan ZHAO
AU - Wei-Ping ZHU
PY - 2022
DO - 10.1587/transfun.2021EAL2061
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E105-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2022
AB - The energy efficiency of intelligent reflecting surface (IRS) enabled internet of things (IoT) networks is studied in this letter. The energy efficiency is mathematically expressed, respectively, as the number of reflecting elements and the spectral efficiency of the network and is shown to scale in the logarithm of the reflecting elements number in the high regime of transmit power from source node. Furthermore, it is revealed that the energy efficiency scales linearly over the spectral efficiency in the high regime of transmit power, in contrast to conventional studies on energy and spectral efficiency trade-offs in the non-IRS wireless IoT networks. Numerical simulations are carried out to verify the derived results for the IRS enabled IoT networks.
ER -