Abstract
Applications of Unmanned aerial vehicles (UAVs) have advanced rapidly in recent years. The UAVs are used for a variety of applications, including surveillance, disaster management, precision agriculture, weather forecasting, etc. In near future, the growing number of UAV applications would necessitate densification of UAV infrastructure (ground radio station (GRS) and ground control station (GCS)) at the expense of increased energy consumption for UAV communications. Maximizing the energy efficiency of this UAV infrastructure is important. Motivated by this, we propose joint resource allocation and UAV scheduling with GRS sleeping. Further, we propose the use of coordinated multi-point (CoMP) with joint transmission (JT) and non-orthogonal multiple access (NOMA) along with GRS sleeping to increase the coverage and data rates, respectively. We then present exhaustive simulation results showcasing the trade-off between throughput and energy efficiency with varying UAV densities. We also compare the coverage, throughput, and energy efficiency for NOMA, CoMP with JT and the benchmark scenario.
Highlights
Now-a-days, Drones are being used in a wide variety of applications like surveillance, disaster management, communication, weather forecast, wildlife monitoring, aerial photography, shipping and delivery, 3D mapping [1]
Where, the power from the GRS g over a sub-channel m, Pmg is given in (1), the channel gain hmp,g is given in (3), Pmghmp,gg ∈G /g is the aggregate interference received by the unmanned aerial vehicles (UAVs) p on the sub-channel m from all other GRSs, and ζb is the fraction of total power allocated to higher channel gain UAV by the GRS g in non-orthogonal multiple access (NOMA) pair b
We present dynamic GRS sleeping with NOMA
Summary
Now-a-days, Drones are being used in a wide variety of applications like surveillance, disaster management, communication, weather forecast, wildlife monitoring, aerial photography, shipping and delivery, 3D mapping [1]. Motivated by it, this is the first work that explores GRSS for energy efficient UAV communication network. The trade-off between energy, coverage, throughput for GRSS, joint GRSS and CoMP, and joint GRSS and NOMA considering the mobility of the UAV has not been much discussed in the literature. This is the motivation of our work.
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