4.8 Article

Joint UAV Hovering Altitude and Power Control for Space-Air-Ground IoT Networks

期刊

IEEE INTERNET OF THINGS JOURNAL
卷 6, 期 2, 页码 1741-1753

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2018.2875493

关键词

Cross-tier interference; heterogeneous networks; Internet of Things (IoT) network; power control; satellite; unmanned aerial vehicle (UAV) communication networks

资金

  1. NSF China [61822104, 61471025, 61771044]
  2. new strategic industries development projects of Shenzhen City [JCYJ20170816151922176]
  3. Young Elite Scientist Sponsorship Program by CAST [2016QNRC001]
  4. Pre-Research Fund of Equipments of MoE of China [6141A02022615]
  5. Co-Research with the Fifth Research Institute of CAST [Co-20180605-47]
  6. Research Foundation of Ministry of Education of China [MCM20170108]
  7. China Mobile [MCM20170108]
  8. Beijing Natural Science Foundation [L172025, L172049]
  9. 111 Project [B170003]
  10. Fundamental Research Funds for the Central Universities [FRF-GF-17-A6, RC1631]

向作者/读者索取更多资源

Unmanned aerial vehicles (UAVs) have been widely used in both military and civilian applications. Equipped with diverse communication payloads, UAVs cooperating with satellites and base stations constitute a space-air-ground three-tier heterogeneous network, which are beneficial in terms of both providing the seamless coverage as well as of improving the capacity for increasingly prosperous Internet of Things networks. However, cross-tier interference may be inevitable among these tightly embraced heterogeneous networks when sharing the same spectrum. The power association problem in satellite, UAV and macrocell three-tier networks becomes a critical issue. In this paper, we propose a two-stage joint hovering altitude and power control solution for the resource allocation problem in UAV networks considering the inevitable cross-tier interference from space-air-ground heterogeneous networks. Furthermore, Lagrange dual decomposition and concave-convex procedure method are used to solve this problem, followed by a low-complexity greedy search algorithm. Finally, simulation results show the effectiveness of our proposed two-stage joint optimization algorithm in terms of UAV network's total throughput.

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