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UAV-Aided Networks for Emergency Communications in Areas with Unevenly Distributed Users

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Journal of Communications and Information Networks

Abstract

Nowadays, daily human life is closely intertwined with various networks. When natural disasters or malicious attacks break out, the failure of communication infrastructure due to direct destruction or indirect impact tends to cause a massive outage of communications. Emergency communication networks play a significant role in rescue operations. Recently, a flexible and efficient solution has been provided for emergency communications using unmanned aerial vehicles (UAVs). By means of their excellent characteristics, UAVs, serving as aerial base stations (ABSs), can be rapidly deployed to temporarily rebuild a damaged communication network to restore the users’ connectivity. In this study, we investigate the use of UAVs as ABSs for an emergency communication scene where user equipment is unevenly distributed and the communication infrastructure has completely failed due to a severe disaster. Effective communication probability (ECP), which integrates throughput coverage and connectivity, is used to evaluate the performance of a communication network. Through simulations, we analyze communication improvements that can be obtained by the flexible deployment of ABSs. The results show a noticeable increase in ECP when some ABSs are deployed in optimal locations.

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Author information

Authors and Affiliations

  1. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, 310027, China

    Gaozhao Peng & Yongxiang Xia

  2. School of Electronic and Information Engineering, Beihang University, Beijing, 100191, China

    Xuejun Zhang & Lin Bai

Authors
  1. Gaozhao Peng
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  2. Yongxiang Xia
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  3. Xuejun Zhang
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  4. Lin Bai
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Corresponding author

Correspondence to Yongxiang Xia.

Additional information

This work was supported by the National Natural Science Foundation of China (No. 61573310). The associate editor coordinating the review of this paper and approving it for publication was W. Zhang.

Gaozhao Peng was born in China. He received his B.E. degree in electronic engineering from Zhejiang University, China. He is now a master student at Zhejiang University. His research interests include UAVaided communication networks.

Yongxiang Xia [corresponding author] received his B.Eng. and Ph.D. degrees in electronic engineering in 1998 and 2004, respectively, both from Tsinghua University, Beijing, China. He is currently an associate professor with Zhejiang University. Dr. Xia’s research is in the area of network science and its applications in engineering networks, where he has published more than 40 papers. He is a member of IEEE Technical Committee on Nonlinear Circuits and Systems, an associate editor of IEEE Transactions on Circuits and Systems II: Express Briefs, and an editorial board member of Scientific Reports.

Xuejun Zhang received his B.S. and Ph.D. degrees from Beihang University in 1994 and 2000, respectively. He is currently a professor with the School of Electronic and Information Engineering, Beihang University. He is the deputy director of National Key Laboratory of CNS/ATM, the director of Beijing Key Laboratory for Network-based Cooperative Air Traffic Management, and the director of Beijing Laboratory for General Aviation Technology. Prof. Zhang’s research interests include the aeronautical data communications, aviation surveillance, and air traffic management. He has published more than 80 SCI and EI indexed papers, obtained 34 national invention patents, won 4 national awards, and 3 provincial/ministerial awards.

Lin Bai received his B.Sc. degree in electronics and information engineering from Huazhong University of Science & Technology, Wuhan, China, in 2004, his M.Sc. (with distinction) degree in communication systems from University of Wales, Swansea, U.K., in 2007, and his Ph.D. degree in advanced telecommunications from the School of Engineering, Swansea University, U.K., in 2010. Since 2011, he has been with the School of Cyber Science and Technology, Beihang University (Beijing University of Aeronautics and Astronautics, BUAA), Beijing, China, as an associate professor and Ph.D. supervisor. Dr. Bai has authored/co-authored 58 SCI-indexed journal papers. He is the author of two books: Low Complexity MIMO Detection and Low Complexity MIMO Receivers published by Springer in 2012 and 2014, respectively. The first book has been cited 95 times according to the Google Scholar, while the chapters have been downloaded over 7 000 times according to the Springer Book Performance Report. His research interests include signal processing of wireless communications, particularly low complexity signal processing and transceiver design of multiple-input multiple-output (MIMO) systems, lattice-based approaches, and non-orthogonal multiple access (NOMA). Dr. Bai received an IEEE Communications Letters Exemplary Reviewers Certificate for 2012 and is a co-winner of Best Student Paper Award from the 13th Annual Integrated Communication, Navigation and Surveillance (ICNS) Conference. Dr. Bai is invited to serve as the symposium co-chair of the 2019 IEEE Global Communications Conference and the tutorial co-chair of the 2019 IEEE/CIC International Conference on Communications in China. He has served as a leading guest editor of IEEE Wireless Communication Magazine special issue on “Space Information Networks” and a guest editor of IEEE Internet of Things Journal special issue on “Unmanned Aerial Vehicular over Internet of Things”. He is an editor or associate editor of several academic journals including IEEE Wireless Communication Letters, IEEE Access, IET Communications, and KSII Transactions on Internet and Information Systems, and the managing editor of Journal of Communications and Information Networks (technical co-sponsored by IEEE ComSoc). He also served as a guest editor of the International Journal of Distributed Sensor Networks from 2012 to 2014. Dr. Bai is a senior member of the IEEE.

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Peng, G., Xia, Y., Zhang, X. et al. UAV-Aided Networks for Emergency Communications in Areas with Unevenly Distributed Users. J. Commun. Inf. Netw. 3, 23–32 (2018). https://doi.org/10.1007/s41650-018-0034-1

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  • DOI: https://doi.org/10.1007/s41650-018-0034-1

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