Zhang, J., Xiang, L., Liu, D., Cui, J., Ng, S.X., Maunder, R.G., Graeupl, T., Carsten-Fiebig, U. and Hanzo, L., 2021. Semi-Stochastic Aircraft Mobility Modelling for Aeronautical Networks: An Australian Case-Study Based on Real Flight Data. IEEE Transactions on Vehicular Technology, 70 (10), 10763-10779.
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Abstract
Terrestrial Internet access is gradually becoming the norm across the globe. However, there is a growing demand for Internet access of passenger airplanes. Hence, it is essential to develop aeronautical networks above the clouds. Therefore the conception of an aircraft mobility model is one of the prerequisite for aeronautical network design and optimization. However, there is a paucity of realistic aircraft mobility models capable of generating large-scale flight data. To fill this knowledge-gap, we develop a semi-stochastic aircraft mobility model based on large-scale real historical Australian flights acquired both on June 29th, 2018 and December 25th, 2018, which represent the busiest day and the quietest day of 2018, respectively. The semi-stochastic aircraft mobility model is capable of generating an arbitrary number of flights, which can emulate the specific features of aircraft mobility. The semi-stochastic aircraft mobility model was then analysed and validated both by the physical layer performance and network layer performance in the case study of Australian aeronautical networks, demonstrating that it is capable of reflecting the statistical characteristics of the real historical flights.
Item Type: | Article |
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ISSN: | 0018-9545 |
Additional Information: | Funding Agency: L. Hanzo would like to acknowledge the financial support of the Engineering and Physical Sciences Research Council projects EPP0342841 and EPP0039901 COALESCE as well as of the European Research Councils Advanced Fellow Grant QuantCom Grant No. 789028 |
Uncontrolled Keywords: | Atmospheric modeling; Data models; Airplanes; Europe; Ad hoc networks; Topology; Analytical models |
Group: | Faculty of Science & Technology |
ID Code: | 35880 |
Deposited By: | Symplectic RT2 |
Deposited On: | 09 Aug 2021 15:33 |
Last Modified: | 14 Mar 2022 14:29 |
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