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In the last decade, drones became frequently used to provide eye-in-the-sky overview in the outdoor environment. Their main advantage compared to the other types of robots is that they can fly above obstacles and rough terrains and they can quickly cover large areas. These properties also open a new application; drones could provide a multi-hop, line of sight communication for groups of ground users. The aim of this thesis is to develop a drone team that will establish wireless ad-hoc network between users on the ground and distributively adapt links and spatial arrangement to the requirements and motion of the ground users. For this application, we use fixed wing drones. Such platforms can be easily and quickly deployed. Fixed wing drones have higher forward speed and higher battery life than hovering platforms. On the other hand, fixed wing drones have unicycle dynamics with constrained forward speed which makes them unable to hover or perform sharp turns. The first challenge consists in bridging unicycle dynamics of the fixed wing drones. Some control strategies have been proposed and validated in simulations using the average distance between the target and the drone as a performance metric. However, besides the distance metric, energy expenditure of the flight also plays an important role in assessing the overall performance of the flight. We propose a new methodology that introduces a new metric (energy expenditure), we compare existing methods on a large set of target motion patterns and present a comparison between the simulation and field experiments on proposed target motion patterns. The second challenge consists in developing a formation control algorithm that will allow fixed wing robots to provide a wide area coverage and to relay data in a wireless ad-hoc network. In such applications fixed wing drones have to be able to regulate an inter-drone distance. Their reduced maneuverability presents the main challenge to design a formation algorithm that will regulate an inter-drone distance. To address this challenge, we present a distributed control strategy that relies only on local information. Each drone has its own virtual agent, it follows the virtual agent by performing previously evaluated and selected target tracking strategy, and flocking interaction rules are implemented between virtual agents. It is shown in simulation and in field experiments with a team of fixed wing drones that using this distributed formation algorithm, drones can cover an area by creating an equilateral triangular lattice and regulate communication link quality between neighboring drones. The third challenge consists in allowing connectivity between independently moving ground users using fixed wing drone team. We design two distributed control algorithms that change drones' spatial arrangement and interaction topology to maintain the connectivity. We propose a potential field based strategy which adapts distance between drones to shrink and expand the fixed wing drones' formation. In second approach, market-based adaptation, drones distributively delete interaction links to expand the formation graph to a tree graph. In simulations and field experiments we show that our proposed strategies successfully maintain independently moving ground users connected. Overall, this thesis presents synthesis of distributed algorithms for fixed wing drones to establish and maintain wireless ad-hoc communication networks.