The explosive growth of the mobile devices and delay-sensitive application make a burden to the current terrestrial network system. Moreover, there are fewer base stations in the rural and hilly regions; therefore, it is difficult for users to get communication services with a high data rate. It is so impossible to get wireless services for the mobile users in the deep sea and disaster areas where the terrestrial base stations do not exist and already collapse. In those areas, deployment of unmanned aerial vehicles (UAVs) as moving base stations and integrate with the satellites (i.e., LEO and GEO satellites), so called integrated space-air-round networks, become mainstream because of its flexible and low deployment cost.
- The optimal deployment of UAVs to get the maximum coverage area and strong wireless signal strength with low co-channel interference.
- Controlling the trajectory of the UAVs to make sure the safety distance between UAVs and the optimal resources (i.e., bandwidth, and power) allocation to get the maximum data rate by taking into account the energy constraint of the UAVs.
- Considering the optimal user association with the UAVs to achieve the highest rate.
- Space-Air-Ground channel modeling.
- Liu, J., Shi, Y., Fadlullah, Z. M., & Kato, N. (2018). Space-air-ground integrated network: A survey. IEEE Communications Surveys & Tutorials, 20(4), 2714-2741.
- Zhang, N., Zhang, S., Yang, P., Alhussein, O., Zhuang, W., & Shen, X. S. (2017). Software defined space-air-ground integrated vehicular networks: Challenges and solutions. IEEE Communications Magazine, 55(7), 101-109.
- Kato, N., Fadlullah, Z. M., Tang, F., Mao, B., Tani, S., Okamura, A., & Liu, J. (2019). Optimizing space-air-ground integrated networks by artificial intelligence. IEEE Wireless Communications, 26(4), 140-147.
- Zhao, B., Liu, P., Wang, X., & You, I. (2019). Toward efficient authentication for space-air-ground integrated Internet of things. International Journal of Distributed Sensor Networks, 15(7), 1550147719860390.