Nowadays, the introduction of unmanned aerial vehicles (UAVs), known as drones, into the wireless networks technology has launched a lot of new opportunities to meet the capacity and coverage requirements that will be likely seen in future wireless networks.
Currently, harnessing UAVs as flying base stations (BSs) also helped achieving a cost-effective and on-the-go wireless network that can be used in many different scenarios – mostly supporting disaster responses and being placed in temporary hotspots.
A new paper is actually looking into this matter in detail – specifically focusing on the integration of drones into the existing wireless networks through a stochastic geometry approach.
The authors of the paper start by addressing the benefits of UAV-aided wireless networks as a key enabler to support diverse applications in orders-of-magnitude and higher capacity requirements as seen in future wireless networks.
According to the authors, the continuous reduction in the cost of UAVs makes these networks cost-effective for wireless operators looking to deploy UAV BSs in emergency situations or complementing existing networks.
As an excerpt from the paper reads:
“UAV aided wireless networks are considered a key enabler to support diverse applications with orders-of-magnitude higher capacity requirements foreseen in future wireless networks. The continuous reduction in the cost of UAVs has made it cost-effective for the wireless operators to deploy UAV BSs in emergency situations and/or to complement existing networks. The wide range of operating altitude of UAVs suggests its usage for relaying transmission between two terrestrial BSs where direct line-of-sight (LOS) is not available, the HO rate in a highly dense heterogeneous network can be a performance limiting factor, we propose to split the control and data plane and assign the control management to the UAV BSs, which due to their high altitudes have the greater coverage.”
Even though the integration of UAV BSs into the existing networks is realized via heterogeneity and BS densification, the capacity gains are achieved at the expense of increased rates. The paper introduces a lot of formulas, concepts and equations in which this model is reviewed and properly allocated.
The authors are also analyzing the rate performance of mobile and stationary users in three tier conventional and C/D split network architectures. From the results, they come up with a clear conclusion:
“In this paper, we consider a UAV aided three tier downlink network and study the rate performance for mobile and stationary users. In particular, we incorporate the effect of handover rates in the user rate and compare the rate performance in the joint C/D and split operating modes. The numerical results show comparable performance for the stationary users but advocate the usage of C/D split scheme for the mobile users. Moreover, a turning point is shown where the handover cost degrades the network performance despite increasing the BSs intensity.”
In the end, it is safe to conclude that the UAV base stations (BSs) are the main subject in this paper – as potentially helping in the increase of area spectral efficiency while adding network heterogeneity and densification.
The authors successfully shed light on the tradeoff mentioned above – analyzing and studying a three-tier network architecture that consists of macro, small and UAV base stations while analyzing its coverage and rate performance.
Even though the joint and split architectures offer similar performance for stationary users, their results showed that a split of the control and data stations for mobile users is more than needed.
Citation: Integrating UAVs into Existing Wireless Networks: A Stochastic Geometry Approach, Rabe Arshad, Lutz Lampe, Hesham ElSawy, Md. Jahangir Hossain – https://arxiv.org/abs/1810.07801, arXiv:1810.07801 [cs.NI]