MAC layer performance modelling for IEEE 802.15.7 based on discrete‐time Markov chain

Abstract Potential lack of enough wireless frequency spectrum has guided researchers towards visible light communication (VLC), emerging as a sturdy support to Wi‐Fi. Though the IEEE 802.15.7 standard has comprehensive medium access control (MAC) and physical (PHY) layer specifications, the emerging...

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Main Authors: Monica Bhutani, Brejesh Lall, Abhishek Dixit
Format: Article
Language:English
Published: Wiley 2021-08-01
Series:IET Communications
Online Access:https://doi.org/10.1049/cmu2.12199
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spelling doaj-fabec55581f145888469371538e36ea52021-08-05T03:42:44ZengWileyIET Communications1751-86281751-86362021-08-0115141883189610.1049/cmu2.12199MAC layer performance modelling for IEEE 802.15.7 based on discrete‐time Markov chainMonica Bhutani0Brejesh Lall1Abhishek Dixit2Indian Institute of Technology Bharati Vidyapeeth's College of Engineering New DelhiElectrical Department Indian Institute of Technology New DelhiElectrical Department Indian Institute of Technology New DelhiAbstract Potential lack of enough wireless frequency spectrum has guided researchers towards visible light communication (VLC), emerging as a sturdy support to Wi‐Fi. Though the IEEE 802.15.7 standard has comprehensive medium access control (MAC) and physical (PHY) layer specifications, the emerging VLC technology still faces MAC challenges. Further, throughput is one of the major concerns for the VLC personal area network (VPAN) as it directly impacts the network speed. We propose a novel Markov chain model with two clear channel assessments, which proves to be a significant milestone in improving the network throughput for a star topology VPAN. This paper extends the already available analytical models for the MAC layer to efficiently plan and predict the VPAN performance. We also extensively evaluate other network metrics, like network collision probability and end‐to‐end epoch, to demonstrate the proposed model's applicability. We verify the model's analytical results with elaborate MATLAB simulations and obtain good estimation, especially for large network sizes.https://doi.org/10.1049/cmu2.12199
collection DOAJ
language English
format Article
sources DOAJ
author Monica Bhutani
Brejesh Lall
Abhishek Dixit
spellingShingle Monica Bhutani
Brejesh Lall
Abhishek Dixit
MAC layer performance modelling for IEEE 802.15.7 based on discrete‐time Markov chain
IET Communications
author_facet Monica Bhutani
Brejesh Lall
Abhishek Dixit
author_sort Monica Bhutani
title MAC layer performance modelling for IEEE 802.15.7 based on discrete‐time Markov chain
title_short MAC layer performance modelling for IEEE 802.15.7 based on discrete‐time Markov chain
title_full MAC layer performance modelling for IEEE 802.15.7 based on discrete‐time Markov chain
title_fullStr MAC layer performance modelling for IEEE 802.15.7 based on discrete‐time Markov chain
title_full_unstemmed MAC layer performance modelling for IEEE 802.15.7 based on discrete‐time Markov chain
title_sort mac layer performance modelling for ieee 802.15.7 based on discrete‐time markov chain
publisher Wiley
series IET Communications
issn 1751-8628
1751-8636
publishDate 2021-08-01
description Abstract Potential lack of enough wireless frequency spectrum has guided researchers towards visible light communication (VLC), emerging as a sturdy support to Wi‐Fi. Though the IEEE 802.15.7 standard has comprehensive medium access control (MAC) and physical (PHY) layer specifications, the emerging VLC technology still faces MAC challenges. Further, throughput is one of the major concerns for the VLC personal area network (VPAN) as it directly impacts the network speed. We propose a novel Markov chain model with two clear channel assessments, which proves to be a significant milestone in improving the network throughput for a star topology VPAN. This paper extends the already available analytical models for the MAC layer to efficiently plan and predict the VPAN performance. We also extensively evaluate other network metrics, like network collision probability and end‐to‐end epoch, to demonstrate the proposed model's applicability. We verify the model's analytical results with elaborate MATLAB simulations and obtain good estimation, especially for large network sizes.
url https://doi.org/10.1049/cmu2.12199
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AT brejeshlall maclayerperformancemodellingforieee802157basedondiscretetimemarkovchain
AT abhishekdixit maclayerperformancemodellingforieee802157basedondiscretetimemarkovchain
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