Drone Positioning for User Coverage Maximization

Aerial base stations (BSs) based on unmanned aerial vehicles (UAVs) can provide rapid wireless services to users in areas without ground infrastructure. This paper aims to deploy multiple aerial BSs to cover a maximum number of ground users within a certain target area while avoiding inter-cell interference (ICI). Two techniques are proposed. The first method deploys multiple aerial BSs in a successive way and converts the non-convex constraints into various linear constraints which can be easily solved. The second method simultaneously deploys multiple aerial BSs by dividing the target area into K convex subareas with the help of K-means clustering. Simulation results show that both techniques achieve a performance gain compared to the benchmark circle packing theory (CPT)

Dynamic Base Station Repositioning to Improve Spectral Efficiency of Drone Small Cells

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.Comment: Accepted at IEEE WoWMoM 2017 - 9 pages, 2 tables, 4 figure

Dynamic Standalone Drone-Mounted Small Cells

This paper investigates the feasibility of Dynamic Horizontal Opportunistic Positioning (D-HOP) use in Drone Small Cells (DSCs), with a central analysis on the impact of antenna equipment efficiency onto the optimal DSC altitude that has been chosen in favor of maximizing coverage. We extend the common urban propagation model of an isotropic antenna to account for a directional antenna, making it dependent on the antenna's ability to fit the ideal propagation pattern. This leads us to define a closed-form expression for calculating the Rate improvement of D-HOP implementations that maintain constant coverage through antenna tilting. Assuming full knowledge of the uniformly distributed active users' locations, three D-HOP techniques were tested: in the center of the Smallest Bounding Circle (SBC); the point of Maximum Aggregated Rate (MAR); and the Center-Most Point (CMP) out of the two aforementioned. Through analytic study and simulation we infer that DSC D-HOP implementations are feasible when using electrically small and tiltable antennas. Nonetheless, it is possible to achieve average per user average rate increases of up to 20-35% in low user density scenarios, or 3-5% in user-dense scenarios, even when using efficient antennas in a DSC that has been designed for standalone coverage.Comment: To be published in proceedings of EuCNC'2

Mobile Network Access Points using Self Organising Drone Constellations

Nowadays with artificial intelligence and automation requires much remote sensing. Sensors can be fixed or mobile. Mobile sensor networks are easy to deploy in a new location however, one of the challenges is figuring out how to interconnect these mobile sensors and link them to a core network. This paper proposes a technique of setting a mobile network that miniature base stations or access points be carried by drones in an automatically structured constellation to enable network connectivity between sensors. The paper presents a swing and adjusting technique to determine the ideal deployment of mobile base stations carried by drones, one base station per drone to connect as many sensors as possible without having prior information on sensor distribution. Swing and adjusting, coverage control, collision avoidance, and self-organizing drone constellation are all part of the algorithm. The suggested approach shows promising results according to simulations