Wang, Y. orcid.org/0000-0002-1357-5255, Chen, C. orcid.org/0000-0002-5161-8973
, Zheng, H. orcid.org/0000-0001-6695-9714
et al. (1 more author)
(2023)
Performance of indoor small-cell networks under interior wall penetration losses.
IEEE Internet of Things Journal, 10 (12).
pp. 10907-10915.
ISSN 2327-4662
Abstract
The performance of indoor small-cell networks (SCNs) is affected by the indoor environment, such as walls, blockages, etc. In this article, we investigate the effect of interior wall attenuation on the performance of an indoor SCN. Specifically, the spatial distribution of interior walls is modeled based on the random shape theory, and the indoor base stations (BSs) are distributed following a homogeneous Poisson point process. The channel model includes the path loss, Rayleigh fading, and wall attenuation. We analytically derive the downlink coverage probability under the strongest received signal user association strategy, which is validated by Monte Carlo simulations for three typical interior wall layouts (i.e., random layout, binary orientation layout, and Manhattan grid). The analytical results show that for a given density of interior walls and signal strength attenuation per wall, there is an optimal BS density that maximizes the coverage probability, and the optimal BS density increases as the wall attenuation increases.
Metadata
Item Type: | Article |
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Authors/Creators: | |
Copyright, Publisher and Additional Information: | © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Coverage probability; indoor; small-cell network (SCN); stochastic geometry; user association strategy; wall blockage |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - HORIZON 2020 778305 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 11 Jul 2023 14:50 |
Last Modified: | 02 Feb 2024 01:13 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/jiot.2023.3241759 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:201468 |