Onireti, O. , Zhang, L. , Imran, A. and Imran, M. A. (2020) Outage probability in the uplink of multitier millimeter wave cellular networks. IEEE Systems Journal, 14(2), pp. 2520-2531. (doi: 10.1109/JSYST.2020.2965001)
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207300.pdf - Published Version Available under License Creative Commons Attribution. 1MB |
Abstract
In this article, using the stochastic geometry, we develop a tractable uplink modeling framework for the outage probability of the multitier millimeter wave (mmWave) cellular networks. Each tier’s mmWave base stations (BSs) are randomly located and they have particular spatial density, antenna gain, receiver sensitivity, blockage parameter, and pathloss exponents. Our model takes account of the maximum power limitation and the per-user power control. More specifically, each user, which could be in line-of-sight (LOS) or non-LOS to its serving mmWave BS, controls its transmit power such that the received signal power at its serving BS is equal to a predefined threshold. Hence, a truncated channel inversion power control scheme is implemented for the uplink of mmWave cellular networks. We derive closed-form expressions for the signal-to-interference-plus-noise-ratio (SINR) outage probability for the uplink of the multitier mmWave cellular networks, which we later degrade to the single-tier network. Furthermore, we analyze the case with a dense network by utilizing the simplified model, where the LOS region is approximated as a fixed LOS disk. The results show that imposing a maximum power constraint on the user significantly affects the SINR outage probability in the uplink of mmWave cellular networks.
| Item Type: | Articles |
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| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Imran, Professor Muhammad and Zhang, Professor Lei and Onireti, Oluwakayode |
| Authors: | Onireti, O., Zhang, L., Imran, A., and Imran, M. A. |
| College/School: | College of Science and Engineering > School of Engineering College of Science and Engineering > School of Engineering > Systems Power and Energy |
| Journal Name: | IEEE Systems Journal |
| Publisher: | IEEE |
| ISSN: | 1932-8184 |
| ISSN (Online): | 1937-9234 |
| Published Online: | 27 January 2020 |
| Copyright Holders: | Copyright © 2020 IEEE |
| First Published: | First published in IEEE Systems Journal 14(2): 2520-2531 |
| Publisher Policy: | Reproduced under a Creative Commons License |
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