Coverage analysis of blockchain-enabled wireless IoMT networks

Xuran LI, Hong-ning DAI, Jie TIAN, Dehuan WAN, Dengwang LI

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

1 Citation (Scopus)

Abstract

The blockchain-enabled wireless Internet of medical things (IoMT) system has recently drawn extensive attention due to the provision of highly-secured healthcare services. However, multiple simultaneous transmissions in blockchain-enabled IoMT (BC-IoMT) networks can cause interference, consequently degrading the overall performance of the system. It is necessary to investigate the performance of BC-IoMT networks. In this paper, we propose a novel analytical framework for wireless BCIoMT networks with consideration of both the spatial model on geographical random distribution of IoMT users and the temporal model on stochastic nature of data block transmission. With this framework, we derive a closed-form expression of the coverage probability in the wireless BC-IoMT network. Our extensive simulation results verify the accuracy of our theoretical analysis. From the analytical framework, we find that the path loss effect, the number of interfering medical sensor devices, and the threshold of successful transmission have a significant impact on the coverage performance of wireless BC-IoMT networks.
Original languageEnglish
Title of host publication2021 IEEE Globecom Workshops (GC Wkshps)
PublisherIEEE
Pages1-5
Number of pages5
ISBN (Electronic)9781665423908
ISBN (Print)9781665423915
DOIs
Publication statusPublished - 24 Jan 2022
Event2021 IEEE Globecom Workshops (GC Wkshps) - Madrid, Spain
Duration: 7 Dec 202111 Dec 2021
https://globecom2021.ieee-globecom.org/

Publication series

Name2021 IEEE Globecom Workshops, GC Wkshps 2021 - Proceedings

Conference

Conference2021 IEEE Globecom Workshops (GC Wkshps)
Country/TerritorySpain
Period7/12/2111/12/21
Internet address

Bibliographical note

Funding Information:
2019QYTPY020), Macao Science and Technology Development Fund under Grant No. 0026/2018/A1 and Hong Kong Institute of Business Studies (HKIBS) Research Seed Fund with Grant No. HKIBS RSF-212-004.

Funding Information:
ACKNOWLEDGEMENT This work was funded by the National Natural Science Foundation of China (61971271), the Taishan Scholars Project of Shandong Province (Tsqn20161023), the Primary Research and Development Plan of Shandong Province (No.

Publisher Copyright:
© 2021 IEEE.

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