Enhancing the Performance of UAV Communications in Cellular Networks

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School of Electrical Engineering | Doctoral thesis (article-based) | Defence date: 2022-11-04
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Authors

Date

2022

Department

Tietoliikenne- ja tietoverkkotekniikan laitos
Department of Communications and Networking

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Mcode

Degree programme

Language

en

Pages

140 + app. 90

Series

Aalto University publication series DOCTORAL THESES, 138/2022

Abstract

The use of cellular networks as a communication infrastructure for Unmanned Aerial Vehicles (UAVs) has become the current trend. This would mainly enable beyond visual line-of-sight applications and allow UAVs to benefit from the latest evolutions achieved in cellular networks.Despite the advantages that cellular networks can bring to UAVs, several issues still need to be addressed. Indeed, cellular networks are deployed to serve ground user equipment (UEs), whereas UAVs' aerial communications are characterized by different channel conditions. Field evaluations have shown that flying UAVs can experience poor link quality, or even negatively affect ground communication. In addition, UAV applications can be deployed in a challenging environment characterized by different types of QoS (Quality of Services). For instance, UAVs can be deployed to provide network connectivity to ground devices, whereas each one of the latter requires sending two types of traffics with different QoS, at the same time. Furthermore, the consideration of cellular networks for UAVs can bring more opportunities that merit to be explored to enhance the communications, mainly in terms of taking advantage of the presence of several UAVs and Mobile Network Operators (MNOs). The main objective of the dissertation is to contribute to enhancing the performance of UAV communications in cellular networks. The contributions of this dissertation can be divided into six categories. First, as aerial communication presents different channel conditions, we are interested in modeling UAV communications in cellular networks and deriving expressions that define the performance indicators. All the contributions build from these expressions, and target performing network optimization to enhance UAV communications in cellular networks. Second, we consider a cellular network deployed to serve both UEs and UAVs, and we investigate their co-existence by enhancing their underlying performances. Next, we focus on supporting the co-existence of several QoS types in UAV communications. To this end, we consider the scenario where UAVs are deployed to provide network connectivity to ground devices, where each one of the latter requires two different QoS types. In the fourth and the fifth categories, we focus on new opportunities that cellular networks can bring to UAV communications. In particular, we investigate the possibility of taking advantage of the presence of several UAVs and MNOs in a way to enhance the performance of UAV communications. Finally, we explore the use of machine learning in order to enable fast optimization and enhance the performance of UAV communications. All the contributions of this dissertation have been validated with a series of performance evaluations.

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Supervising professor

Manner, Jukka, Prof., Aalto University, Department of Communications and Networking, Finland

Thesis advisor

Chelli, Ali, Prof., University of South-Eastern Norway, Norway
Bagaa, Miloud, Dr., Aalto University, Finland

Keywords

unmanned aerial vehicles, wireless networks, radio resource allocation

Other note

Parts

  • [Publication 1]: H. Hellaoui, A. Chelli, M. Bagaa, T. Taleb, “Towards Mitigating the Impact of UAVs on Cellular Communications,” In 2018 IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, United Arab Emirates, pp. 1-7, Dec 2018.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201904022466
    DOI: 10.1109/GLOCOM.2018.8648083 View at publisher
  • [Publication 2]: H. Hellaoui, O. Bekkouche, M. Bagaa, T. Taleb, “Aerial control system for spectrum efficiency in UAV-to-cellular communications,” IEEE Communications Magazine, vol. 56, no. 10, pp. 108-113, 2018.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201811095687
    DOI: 10.1109/MCOM.2018.1800078 View at publisher
  • [Publication 3]: H. Hellaoui, A. Chelli, M. Bagaa, T. Taleb, M. Pätzold, “Towards efficient control of mobile network-enabled UAVs,” In 2019 IEEE Wireless Communications and Networking Conference (WCNC), Marrakesh, Morocco, pp. 1-6, Dec 2019.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-202001021181
    DOI: 10.1109/WCNC.2019.8885665 View at publisher
  • [Publication 4]: H. Hellaoui, A. Chelli, M. Bagaa, T. Taleb, “Efficient steering mechanism for mobile network-enabled uavs,” In 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, pp. 1-6, Dec 2019.
    DOI: 10.1109/GLOBECOM38437.2019.9014131 View at publisher
  • [Publication 5]: H. Hellaoui, A. Chelli, M. Bagaa, T. Taleb, “UAV communication strategies in the next generation of mobile networks,” In 2020 International Wireless Communications and Mobile Computing (IWCMC), Limassol, Cyprus, pp. 1-6, June 2020.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-202009045267
    DOI: 10.1109/IWCMC48107.2020.9148312 View at publisher
  • [Publication 6]: H. Hellaoui, M. Bagaa, A. Chelli, T. Taleb, “Joint Sub-Carrier and Power Allocation for Efficient Communication of Cellular UAVs,” IEEE Transactions on Wireless Communications (TWC), vol. 19, no. 12, pp. 8287-8302, 2020.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-202010025763
    DOI: 10.1109/twc.2020.3021252 View at publisher
  • [Publication 7]: H. Hellaoui, M. Bagaa, A. Chelli, T. Taleb, “On Supporting Multi-Services in UAV-Enabled Aerial Communication for the Internet of Things,” , (submitted), 2021
  • [Publication 8]: H. Hellaoui, B. Yang, T. Taleb, “Towards using Deep Reinforcement Learning for Connection Steering in Cellular UAVs,” In 2021 IEEE Global Communications Conference (GLOBECOM), Madrid, Spain, pp. 1-6, Dec 2021.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-202204192835
    DOI: 10.1109/GLOBECOM46510.2021.9685265 View at publisher

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https://urn.fi/URN:ISBN:978-952-64-0957-3

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[diss] Sähkötekniikan korkeakoulu / ELEC