Dynamic Lognormal Shadowing Framework for the Performance Evaluation of Next Generation Cellular Systems

Performance evaluation tools for wireless cellular systems are very important for the establishment and testing of future internet applications. As the complexity of wireless networks keeps growing, wireless connectivity becomes the most critical requirement in a variety of applications (considered...

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Main Authors: Georgios A. Karagiannis, Athanasios D. Panagopoulos
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Future Internet
Subjects:
Online Access:https://www.mdpi.com/1999-5903/11/5/106
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spelling doaj-e508b261cee343bc9ea6064f8d38db0e2020-11-25T01:38:41ZengMDPI AGFuture Internet1999-59032019-05-0111510610.3390/fi11050106fi11050106Dynamic Lognormal Shadowing Framework for the Performance Evaluation of Next Generation Cellular SystemsGeorgios A. Karagiannis0Athanasios D. Panagopoulos1School of Electrical and Computer Engineering, National Technical University of Athens, GR-15780 Zografou, GreeceSchool of Electrical and Computer Engineering, National Technical University of Athens, GR-15780 Zografou, GreecePerformance evaluation tools for wireless cellular systems are very important for the establishment and testing of future internet applications. As the complexity of wireless networks keeps growing, wireless connectivity becomes the most critical requirement in a variety of applications (considered also complex and unfavorable from propagation point of view environments and paradigms). Nowadays, with the upcoming 5G cellular networks the development of realistic and more accurate channel model frameworks has become more important since new frequency bands are used and new architectures are employed. Large scale fading known also as shadowing, refers to the variations of the received signal mainly caused by obstructions that significantly affect the available signal power at a receiver’s position. Although the variability of shadowing is considered mostly spatial for a given propagation environment, moving obstructions may significantly impact the received signal’s strength, especially in dense environments, inducing thus a temporal variability even for the fixed users. In this paper, we present the case of lognormal shadowing, a novel engineering model based on stochastic differential equations that models not only the spatial correlation structure of shadowing but also its temporal dynamics. Based on the proposed spatio-temporal shadowing field we present a computationally efficient model for the dynamics of shadowing experienced by stationary or mobile users. We also present new analytical results for the average outage duration and hand-offs based on multi-dimensional level crossings. Numerical results are also presented for the validation of the model and some important conclusions are drawn.https://www.mdpi.com/1999-5903/11/5/106wireless channellognormal shadowingstochastic differential equationdynamics5G cellular networks
collection DOAJ
language English
format Article
sources DOAJ
author Georgios A. Karagiannis
Athanasios D. Panagopoulos
spellingShingle Georgios A. Karagiannis
Athanasios D. Panagopoulos
Dynamic Lognormal Shadowing Framework for the Performance Evaluation of Next Generation Cellular Systems
Future Internet
wireless channel
lognormal shadowing
stochastic differential equation
dynamics
5G cellular networks
author_facet Georgios A. Karagiannis
Athanasios D. Panagopoulos
author_sort Georgios A. Karagiannis
title Dynamic Lognormal Shadowing Framework for the Performance Evaluation of Next Generation Cellular Systems
title_short Dynamic Lognormal Shadowing Framework for the Performance Evaluation of Next Generation Cellular Systems
title_full Dynamic Lognormal Shadowing Framework for the Performance Evaluation of Next Generation Cellular Systems
title_fullStr Dynamic Lognormal Shadowing Framework for the Performance Evaluation of Next Generation Cellular Systems
title_full_unstemmed Dynamic Lognormal Shadowing Framework for the Performance Evaluation of Next Generation Cellular Systems
title_sort dynamic lognormal shadowing framework for the performance evaluation of next generation cellular systems
publisher MDPI AG
series Future Internet
issn 1999-5903
publishDate 2019-05-01
description Performance evaluation tools for wireless cellular systems are very important for the establishment and testing of future internet applications. As the complexity of wireless networks keeps growing, wireless connectivity becomes the most critical requirement in a variety of applications (considered also complex and unfavorable from propagation point of view environments and paradigms). Nowadays, with the upcoming 5G cellular networks the development of realistic and more accurate channel model frameworks has become more important since new frequency bands are used and new architectures are employed. Large scale fading known also as shadowing, refers to the variations of the received signal mainly caused by obstructions that significantly affect the available signal power at a receiver’s position. Although the variability of shadowing is considered mostly spatial for a given propagation environment, moving obstructions may significantly impact the received signal’s strength, especially in dense environments, inducing thus a temporal variability even for the fixed users. In this paper, we present the case of lognormal shadowing, a novel engineering model based on stochastic differential equations that models not only the spatial correlation structure of shadowing but also its temporal dynamics. Based on the proposed spatio-temporal shadowing field we present a computationally efficient model for the dynamics of shadowing experienced by stationary or mobile users. We also present new analytical results for the average outage duration and hand-offs based on multi-dimensional level crossings. Numerical results are also presented for the validation of the model and some important conclusions are drawn.
topic wireless channel
lognormal shadowing
stochastic differential equation
dynamics
5G cellular networks
url https://www.mdpi.com/1999-5903/11/5/106
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