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Abstract

The paper addresses the issue of the Electromagnetic Environment Situational Awareness techniques. The main focus is put on sensing and the Radio Environment Map. These two dynamic techniques are described in detail. The Radio Environment Map is considered the essential part of the spectrum management system. It is described how the density and deployment of sensors affect the quality of maps and it is analyzed which methods are the most suitable for map construction. Additionally, the paper characterizes several sensing methods.

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Authors and Affiliations

M. Suchański
P. Kaniewski
K. Kosmowski
M. Kustra
J. Romanik
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Abstract

Radio environment maps (REMs) are beginning to be an integral part of modern mobile radiocommunication systems and networks, especially for ad-hoc, cognitive, and dynamic spectrum access networks. The REMs will use emerging military systems of tactical communications. The REM is a kind of database used at the stage of planning and management of the radio resources and networks, which considers the geographical features of an area, environmental propagation properties, as well as the parameters of radio network elements and available services. At the REM, for spatial management of network nodes, various methods of propagation modeling for determining the attenuation and capacity of wireless links and radio ranges are used. One method of propagation prediction is based on a numerical solution of the wave equation in a parabolic form, which allows considering, i.a., atmospheric refraction, terrain shape, and soil electrical parameters. However, the determination of a current altitudinal profile of atmospheric refraction may be a problem. If the propagation-prediction model uses a fixed refraction profile, then the calibration of this model based on empirical measurements is required. We propose a methodology for calibrating the analyzed model based on an example empirical research scenario. The paper presents descriptions of the propagation model, test-bed and scenario used in measurements, and obtained signal attenuation results, which are used for the initial calibration of the model.

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Authors and Affiliations

Jan M. Kelner
Michał Kryk
Jerzy Łopatka
Piotr Gajewski

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