An Adaptive UAV Network for Increased User Coverage and Spectral Efficiency

© 2019 IEEE. Unmanned Aerial Vehicles (UAVs) are fast becoming a popular choice in a variety of applications in wireless communication systems. UAV-mounted base stations (UAV-BSs) are an effective and cost-efficient solution for providing wireless connectivity where fixed infrastructure is not available or destroyed. We present a method of using UAV-BSs to provide coverage to mobile users in a fixed area. We propose an algorithm for predicting the user locations based on their mobility data and clustering the predicted locations, so that one UAV-BS would provide coverage to one user cluster. The proposed method, hence is similar to the UAV-BSs following the users to keep them under the coverage region. Simulation results show that the proposed method increases the user coverage by 47%-72% and increases the spectral efficiency by 43%-55% depending on the scenario and in addition, reduces the number of UAV-BSs required to provide coverage

Algorithm for energy efficient inter-UAV collision avoidance

© 2017 IEEE. Unmanned Aerial Vehicles (UAV) are fast gaining popularity. Due to their many desired features, in the near future, UAVs will be an inevitable part of many fields. This increased use of UAVs, has given rise to the idea of multi-UAV systems, commonly known as UAV swarms, where a number of UAVs ranging from two to hundreds have to collaborate with each other and perform a common shared task or tasks. When sharing a common air space and flying in close proximity of each other, inter-UAV collision avoidance becomes an important factor in UAV swarms. Thus, for effective use of UAV swarms, it is essential to have an efficient inter-UAV collision avoidance mechanism. Although there are a number of suggested techniques, avoiding inter-UAV collisions while minimising the energy consumption of the UAV system is a challenge. In this paper, a Potential Field Method based algorithm to avoid collisions of a UAV system, considering the minimising of system energy usage, is suggested. We consider the energy consumption of a UAV system to depend on the distance travelled and the turns- A ngular changes, in trajectories. Our method reduces the angular changes in trajectories by an average of 36% and total travel distance by 6-8%. The total time taken to achieve targets is reduced by 3-14% depending on the scenario

Radio environment maps generation and spectrum sensing testbed for spectrum sharing in 5G networks

© 2017 IEEE. To deliver on the data rate and latency promises of 5G, more spectrum resources below 6 GHz are required. Therefore the regulators are now promoting spectrum sharing. Having access to realtime spatio-Temporal spectrum usage information enables efficient decision making and monitoring. This knowledge can be represented in Radio Environment Maps constructed through geolocation aware spectrum measurements. In this paper, we give an overview of the spectrum sharing concept and its emergence in 5G standardisation. We also present our research on spectrum sharing including methods for efficient and accurate generation of Radio Environment Maps and a practical radio spectrum measurements testbed

Potential field based inter-UAV collision avoidance using virtual target relocation

© 2018 IEEE. Unmanned Aerial Vehicles (UAV) are becoming popular in a range of areas. This has given rise to the concept of UAV swarms, where multiple UAVs act together to achieve a common task. With multiple UAVs flying in close proximity to each other, sharing the same airspace, the risk of inter-UAV collisions increases. It's important to avoid these collisions while having minimal impact on the UAV system. We propose a novel Potential Field Method (PFM) based algorithm for inter-UAV collision avoidance which considerably reduces the total time taken by the UAV system to achieve its goal. We control the collision avoidance actions of the UAVs by virtually relocating their targets. The positions of the virtual targets are calculated to minimize the collision probability, based on a probability function we introduced. The proposed algorithm reduces the total system time approximately by 20\% as opposed to the traditional PFM

Comprehensive energy consumption model for unmanned aerial vehicles, based on empirical studies of battery performance

© 2018 IEEE. Unmanned aerial vehicles (UAVs) are fast gaining popularity in a wide variety of areas and are already being used for a range of tasks. Despite their many desirable features, a number of drawbacks hinder the potential of UAV applications. As typical UAVs are powered by on-board batteries, limited battery lifetime is identified as a key limitation in UAV applications. Thus, in order to preserve the available energy, planning UAV missions in an energy efficient manner is of utmost importance. For energy efficient UAV mission planning, it is necessary to predict the energy consumption of specific UAV manoeuvring actions. Accurate energy prediction requires a reliable and realistic energy consumption model. In this paper, we present a consistent and complete energy consumption model for UAVs based on empirical studies of battery usage for various UAV activities. We considered the impact of different flight scenarios and conditions on UAV energy consumption when developing the proposed model. The energy consumption model presented in this paper can be readily used for energy efficient UAV mission planning

Empirical Power Consumption Model for UAVs

© 2018 IEEE. Unmanned Aerial Vehicles (UAV) are gaining popularity in a range of areas and are already being used for a wide variety of purposes. While UAVs have many desirable features, limited battery lifetime is identified as a key restriction in UAV applications. Typical UAVs being electric devices, powered by on-board batteries, this constrain has limited their capabilities to a considerable extent. Thus planning UAV missions in an energy efficient manner is of utmost importance. To achieve this, for prediction of power consumption, it is necessary to have a reliable power consumption model. In this paper, we present a consistent and complete power consumption model for UAVs based on empirical studies of battery usage for various UAV activities. The power consumption model presented in this paper can be readily used for energy efficient UAV mission planning