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

School of Electrical and Computer Engineering, National Technical University of Athens, GR-15780 Zografou, Greece
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Future Internet 2019, 11(5), 106; https://doi.org/10.3390/fi11050106
Received: 22 March 2019 / Revised: 19 April 2019 / Accepted: 29 April 2019 / Published: 2 May 2019
(This article belongs to the Special Issue 10th Anniversary Feature Papers)
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Abstract

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. View Full-Text
Keywords: wireless channel; lognormal shadowing; stochastic differential equation; dynamics; 5G cellular networks wireless channel; lognormal shadowing; stochastic differential equation; dynamics; 5G cellular networks
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Karagiannis, G.A.; Panagopoulos, A.D. Dynamic Lognormal Shadowing Framework for the Performance Evaluation of Next Generation Cellular Systems. Future Internet 2019, 11, 106.

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