With recent advancements in drone technology, researchers are now considering the possibility of deploying small cells served by base stations mounted on flying drones. A major advantage of such drone small cells is that the operators can quickly provide cellular services in areas of urgent demand without having to pre-install any infrastructure. Since the base station is attached to the drone, technically it is feasible for the base station to dynamic reposition itself in response to the changing locations of users for reducing the communication distance, decreasing the probability of signal blocking, and ultimately increasing the spectral efficiency. In this paper, we first propose distributed algorithms for autonomous control of drone movements, and then model and analyse the spectral efficiency performance of a drone small cell to shed new light on the fundamental benefits of dynamic repositioning. We show that, with dynamic repositioning, the spectral efficiency of drone small cells can be increased by nearly 100 for realistic drone speed, height, and user traffic model and without incurring any major increase in drone energy consumption.
Multiple interfering UAVs bring more challenges such as the distance between UAVs. The problem of the optimal deployment of two interfering drone small cells is investigated in @cite_19 . @cite_10 addressed the problem of cell outage or cell overload using UAVs to temporarily offload the traffic to neighbor cells in 4G networks. In that work, a central planning model for the placement of UAV relays was discussed, the feasibility of the solution was also proved using an analytical model.
@cite_19 @cite_10
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Compensating temporary overload or site outage in cellular mobile networks is still an unsolved problem in order to avoid situations where services are unavailable. For this objective, we propose to use a swarm of Unmanned Aerial Vehicles (UAVs) equipped with cellular technology to temporarily offload traffic into neighbouring cells in LTE 4G networks. We discuss relay placement, amount of relays and relay transmit power for overload and outage compensation and provide an analytical model for evaluating system performance in the downlink. We assume that the spatial separation between the aerial service provider, users, and offload eNodeB is beneficial for temporarily increasing spectral efficiency. Our results give evidence, that aerial network provisioning can be used for optimizing mobile networks in overload and outage scenarios. In this paper, the optimal deployment of multiple unmanned aerial vehicles (UAVs) acting as flying base stations is investigated. Considering the downlink scenario, the goal is to minimize the total required transmit power of UAVs while satisfying the users' rate requirements. To this end, the optimal locations of UAVs as well as the cell boundaries of their coverage areas are determined. To find those optimal parameters, the problem is divided into two sub-problems that are solved iteratively. In the first sub-problem, given the cell boundaries corresponding to each UAV, the optimal locations of the UAVs are derived using the facility location framework. In the second sub-problem, the locations of UAVs are assumed to be fixed, and the optimal cell boundaries are obtained using tools from optimal transport theory. The analytical results show that the total required transmit power is significantly reduced by determining the optimal coverage areas for UAVs. These results also show that, moving the UAVs based on users' distribution, and adjusting their altitudes can lead to a minimum power consumption. Finally, it is shown that the proposed deployment approach, can improve the system's power efficiency by a factor of 20 χ compared to the classical Voronoi cell association technique with fixed UAVs locations. With hard requirements of high performance for the next generation mobile communication systems, especially 5G networks, coverage has been the crucial problem which requires the deployment of more stations by the service providers. However, this deployment of new stations is not cost effective and requires network replanning. This issue can easily be overcome by the use of Unmanned Aerial Vehicles (UAVs) in the existing communication system. Thus, considering this as a problem, an intelligent solution is presented for the accurate and efficient placement of the UAVs with respect to the demand areas resulting in the increase in the capacity and coverage of the wireless networks. The proposed approach utilizes the priority-wise dominance and the entropy approaches for providing solutions to the two problems considered in this paper, namely, Macro Base Station (MBS) decision problem and the cooperative UAV allocation problem. Finally, network bargaining is defined over these solutions to accurately map the UAVs to the desired areas resulting in the significant improvement of the network parameters, namely, throughput, per User Equipment (UE) capacity, 5th percentile spectral efficiency, network delays and guaranteed signal to interference plus noise ratio by 6.3 , 16.6 , 55.9 , 48.2 , and 36.99 , respectively in comparison with the existing approaches. In this letter, a novel framework for delay-optimal cell association in unmanned aerial vehicle (UAV)-enabled wireless cellular networks is proposed. In particular, to minimize the average network delay under any arbitrary spatial distribution of the ground users, the optimal cell partitions of the UAVs and terrestrial base stations are determined. To this end, using the powerful mathematical tools of optimal transport theory, the existence of the solution to the optimal cell association problem is proved and the solution space is completely characterized. The analytical and simulation results show that the proposed approach yields substantial improvements in terms of the average network delay.