With the advantages of high mobility, high maneuverability and high probability of line of sight (LoS) transmission, unmanned aerial vehicles (UAVs) have attracted much interest in assisting wireless communication systems. This paper considers a set of ground users cannot receive service from the base station because of a sudden malfunction of the base station, a UAV is deployed in the air to work as a relay to establish communication links between unable users and the neighboring base station. We are going to optimize the UAV relay deployment, aiming to maximize the capacity of the relay network. Considering the channel model and exact positions of ground users are priori unknown, the problem of deployment optimization can't be solved directly because of lacking parameters. Thus, considering multiple detecting UAVs are available and only one is available, model-free online deployment approaches are respectively proposed to solve this challenging problem. The optimal relay deployment is acquired via online learning and iteration without the knowledge of channel model and exact positions of the users but with the real-time measurement of relay capacity, thus the proposed model-free deployment approaches can be adaptive to the practical communication environment compared to the model-based optimization. Simulation results show that with the proposed model-free deployment approaches, relay network capacities are close to the optimum.

Recently, unmanned aerial vehicles (UAVs) have been widely studied in the communication area to work as aerial base stations, due to the high probability of line of sight (LoS) and high flexibility. However, few works consider fairness for the users, which is one of the most important metrics for a network. In this paper, in order to maximize network capacity with the consideration of fairness, trajectory and scheduling of the mobile UAV aerial base station are jointly optimized. Firstly, the problem of maximizing network capacity with the consideration of fairness is formulated. On account of the coupling relationship of trajectory and scheduling, an alternate iteration approach that contains ant colony algorithm and genetic algorithm are then proposed to solve this intractable problem. Finally, the simulation results demonstrate the fairness enhance of the network and the validity and effectiveness of the proposed optimization approach.

With the advantage of high flexibility, unmanned aerial vehicle (UAV) can be deployed in a high height to provide high probability of line-of-sight (LoS) transmission for the ground units. Thus, UAV can bring much gain for communication systems. In this paper, we consider that a set of UAVs are deployed in the air to work as relays to aid the ground device-to-device (D2D) pairs. For the reason that the communication resource on one relay is limited and the positions of the relays are different, network performance is significantly impacted by relay assignment. Considering that there is no central controller in this relay network, centralized relay assignment approaches cannot be used. Thus, we propose a novel decentralized relay selection approach based on relay exchange, aiming to maximize the total capacity of the network. With the proposed approach, the total capacity of the relay network is strictly non-decreasing with the increase of the iteration steps. Numerical results show that the proposed approach have attractive properties.