International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

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 Volume 8, Issue 11 (November 2021), Pages: 119-128

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 Original Research Paper

 Title: 3D placements of drones in a millimeter-wave network to maximize the lifetime of wireless devices

 Author(s): Wa'ed Malkawi *, Hazim Shakhatreh, Ahmed Musa

 Affiliation(s):

 Department of Telecommunications Engineering, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid, Jordan

  Full Text - PDF          XML

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-1227-0302

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2021.11.015

 Abstract:

In the last few years, the use of drones is increasing day by day in wireless networks and the applications of them are rapidly increased on different sides. Now, we can use the drone as an aerial base station (BS) to support cellular networks in emergency cases and in natural disasters. To take the advantage of both drones and fifth-generation (5G) and link between their features, we study an aerial BS considering millimeter waves (mm-waves). In this paper, we optimize the 3D placements for multiple unmanned aerial vehicles (UAVs) in an mm-wave network to achieve maximum time durations of the uplink transmission. First, we present a formulation for the placement problem, where we aim to allocate 3D locations for multiple UAVs to achieve the maximum sum of time durations of uplink transmissions. We propose an efficient algorithm to find the placements of UAVs. We propose an algorithm that starts by grouping the wireless devices into a number of clusters, and each cluster is served by a single UAV. After the clustering process, it applies the gradient projection-based algorithm (GP) or particle swarm optimization (PSO) in each cluster. In the results section, our proposed approach and the center projection algorithm will be compared to prove the efficiency of our approach. 

 © 2021 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: mm-wave, UAV, Maximizing the lifetime, Disaster, Aerial BS

 Article History: Received 7 June 2021, Received in revised form 25 August 2021, Accepted 6 September 2021

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Malkawi W, Shakhatreh H, and Musa A (2021). 3D placements of drones in a millimeter-wave network to maximize the lifetime of wireless devices. International Journal of Advanced and Applied Sciences, 8(11): 119-128

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 Figures

 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9 Fig. 10 Fig. 11

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5

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 References (22)

  1. Akdeniz MR, Liu Y, Samimi MK, Sun S, Rangan S, Rappaport TS, and Erkip E (2014). Millimeter wave channel modeling and cellular capacity evaluation. IEEE Journal on Selected Areas in Communications, 32(6): 1164-1179. https://doi.org/10.1109/JSAC.2014.2328154   [Google Scholar]
  2. Azari MM, Rosas F, Chiumento A, Ligata A, and Pollin S (2018). Uplink performance analysis of a drone cell in a random field of ground interferers. In the IEEE Wireless Communications and Networking Conference, IEEE, Barcelona, Spain: 1-6. https://doi.org/10.1109/WCNC.2018.8377426   [Google Scholar]
  3. Bertsekas DP and Tsitsiklis JN (1989). Parallel and distributed computation: Numerical methods. Prentice-Hall, Inc., New York, USA.   [Google Scholar]
  4. Gapeyenko M, Bor-Yaliniz I, Andreev S, Yanikomeroglu H, and Koucheryavy Y (2018). Effects of blockage in deploying mmWave drone base stations for 5G networks and beyond. In the IEEE International Conference on Communications Workshops, IEEE, Kansas City, USA: 1-6. https://doi.org/10.1109/ICCW.2018.8403671   [Google Scholar]
  5. Gheitanchi S, Ali F, and Stipidis E (2010). Particle swarm optimization for adaptive resource allocation in communication networks. EURASIP Journal on Wireless Communications and Networking, 2010: 465632. https://doi.org/10.1155/2010/465632   [Google Scholar]
  6. Hartigan JA and Wong MA (1979). Algorithm AS 136: A k-means clustering algorithm. Journal of the Royal Statistical Society: Series C (Applied Statistics), 28(1): 100-108. https://doi.org/10.2307/2346830   [Google Scholar]
  7. Jiang X, Zeng WJ, Yasotharan A, So HC, and Kirubarajan T (2014). Quadratically constrained minimum dispersion beamforming via gradient projection. IEEE Transactions on Signal Processing, 63(1): 192-205. https://doi.org/10.1109/TSP.2014.2367464   [Google Scholar]
  8. Khawaja W, Ozdemir O, and Guvenc I (2017). UAV air-to-ground channel characterization for mmWave systems. In the IEEE 86th Vehicular Technology Conference, IEEE, Toronto, Canada: 1-5. https://doi.org/10.1109/VTCFall.2017.8288376   [Google Scholar]
  9. Marini F and Walczak B (2015). Particle swarm optimization (PSO): A tutorial. Chemometrics and Intelligent Laboratory Systems, 149: 153-165. https://doi.org/10.1016/j.chemolab.2015.08.020   [Google Scholar]
  10. Na S, Xumin L, and Yong G (2010). Research on k-means clustering algorithm: An improved k-means clustering algorithm. In the 3rd International Symposium on Intelligent Information Technology and Security Informatics, IEEE, Jian, China: 63-67. https://doi.org/10.1109/IITSI.2010.74   [Google Scholar]
  11. Niu Y, Li Y, Jin D, Su L, and Vasilakos AV (2015). A survey of millimeter wave communications (mmWave) for 5G: Opportunities and challenges. Wireless Networks, 21(8): 2657-2676. https://doi.org/10.1007/s11276-015-0942-z   [Google Scholar]
  12. Sawalmeh A, Othman NS, Shakhatreh H, and Khreishah A (2017). Providing wireless coverage in massively crowded events using UAVs. In the IEEE 13th Malaysia International Conference on Communications, IEEE, Johor Bahru, Malaysia: 158-163. https://doi.org/10.1109/MICC.2017.8311751   [Google Scholar]
  13. Sekander S, Tabassum H, and Hossain E (2018). Multi-tier drone architecture for 5G/B5G cellular networks: Challenges, trends, and prospects. IEEE Communications Magazine, 56(3): 96-103. https://doi.org/10.1109/MCOM.2018.1700666   [Google Scholar]
  14. Shakhatreh H and Khreishah A (2018). Optimal placement of a UAV to maximize the lifetime of wireless devices. In the 14th International Wireless Communications and Mobile Computing Conference, IEEE, Limassol, Cyprus: 1225-1230. https://doi.org/10.1109/IWCMC.2018.8450437   [Google Scholar]
  15. Shakhatreh H and Malkawi W (2020). Maximizing the lifetime of wireless devices in millimeter wave UAV networks. Universal Journal of Electrical and Electronic Engineering, 7(4): 234-241. https://doi.org/10.13189/ujeee.2020.070402   [Google Scholar]
  16. Shakhatreh H, Khreishah A, Alsarhan A, Khalil I, Sawalmeh A, and Othman NS (2017b). Efficient 3D placement of a UAV using particle swarm optimization. In the 8th International Conference on Information and Communication Systems, IEEE, Irbid, Jordan: 258-263. https://doi.org/10.1109/IACS.2017.7921981   [Google Scholar]
  17. Shakhatreh H, Khreishah A, and Ji B (2017a). Providing wireless coverage to high-rise buildings using UAVs. In the IEEE International Conference on Communications, IEEE, Paris, France: 1-6. https://doi.org/10.1109/ICC.2017.7997403   [Google Scholar]
  18. Shakhatreh H, Khreishah A, and Ji B (2019). UAVs to the rescue: Prolonging the lifetime of wireless devices under disaster situations. IEEE Transactions on Green Communications and Networking, 3(4): 942-954. https://doi.org/10.1109/TGCN.2019.2930642   [Google Scholar]
  19. Shakhatreh H, Khreishah A, Othman NS, and Sawalmeh A (2017c). Maximizing indoor wireless coverage using UAVs equipped with directional antennas. In the IEEE 13th Malaysia International Conference on Communications, IEEE, Johor Bahru, Malaysia: 175-180. https://doi.org/10.1109/MICC.2017.8311754   [Google Scholar]
  20. Yang D, Wu Q, Zeng Y, and Zhang R (2018). Energy tradeoff in ground-to-UAV communication via trajectory design. IEEE Transactions on Vehicular Technology, 67(7): 6721-6726. https://doi.org/10.1109/TVT.2018.2816244   [Google Scholar]
  21. Zeng Y, Zhang R, and Lim TJ (2016a). Throughput maximization for UAV-enabled mobile relaying systems. IEEE Transactions on Communications, 64(12): 4983-4996. https://doi.org/10.1109/TCOMM.2016.2611512   [Google Scholar]
  22. Zeng Y, Zhang R, and Lim TJ (2016b). Wireless communications with unmanned aerial vehicles: Opportunities and challenges. IEEE Communications Magazine, 54(5): 36-42. https://doi.org/10.1109/MCOM.2016.7470933   [Google Scholar]