Coverage probability of RIS-assisted mmWave cellular networks under blockages: A stochastic geometric approach

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date

2022-08

Department

Department of Communications and Networking

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Mcode

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Language

en

Pages

9

Series

Physical Communication, Volume 53

Abstract

In this paper, we consider a downlink millimeter-wave (mmWave)-based cellular network where some of the objects in the environment that block the links, such as buildings, are equipped with reflective intelligent surfaces (RISs). Leveraging tools from stochastic geometry, we model the locations of the base stations (BSs) using homogeneous Poisson Point Processes and blockages are modeled by line Boolean model. We consider different path loss exponents for the line of sight (LOS) and non-LOS (NLOS) links. A typical user located at the origin can be served directly with LOS or NLOS BS or by using the RIS relay and a BS. By considering the minimum path loss criteria, after deriving the user association probability with RIS or direct link, we derive the coverage probability of the system using stochastic geometry. Simulation results show that using the RIS results in significant performance improvement especially in the case that the density of the blockages is high. The performance increment is even more substantial for high SINR threshold, e.g. the coverage probability for blockage density of 700 blockages per km2 and SINR threshold of 20dB is twice the case that RISs are not employed.

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Funding Information: This research was supported by the Faculty Development Competitive Research Grant (No. 240919FD3918 ), Nazarbayev University, Kazakhstan . Publisher Copyright: © 2022 Elsevier B.V.

Keywords

Blockage, Coverage probability, Millimeter wave, Reflective intelligent surfaces, Stochastic geometry

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DOI

10.1016/j.phycom.2022.101740

Citation

Bagherinejad, S, Bayanifar, M, Sattari Maleki, M & Maham, B 2022, 'Coverage probability of RIS-assisted mmWave cellular networks under blockages : A stochastic geometric approach', Physical Communication, vol. 53, 101740. https://doi.org/10.1016/j.phycom.2022.101740

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https://urn.fi/URN:NBN:fi:aalto-202302202117

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[article-cris] Sähkötekniikan korkeakoulu / ELEC