Outage minimization of energy-harvesting wireless sensor network supported by UAV

Due to their adaptability, mobility, and capacity to offer an ideal channel, unmanned aerial vehicles (UAVs) have become a potential option for wireless power transfer and data collection in wireless sensor networks (WSNs). This paper examines energy-constrained WSNs, where data transfer to the data center is facilitated by UAV and sensors rely on radio frequency (RF) energy obtained by a Power Beacon (PB). However, due to energy limitations, sensors can only send data using the harvested energy. We consider a WSN in which the nodes are randomly distributed within a circular area, with the PB placed at the center of the WSN. To evaluate the system performance, we consider the dynamic nature of the wireless channel, which includes factors such as signal reflection, scattering, and diffraction. Through numerical analysis and simulations, the main aim is to identify the optimal system parameters that minimize the outage probability. This analysis provides valuable insights for designing more effective and reliable energy-harvesting WSNs with UAV as data collector. By leveraging UAV in WSNs, system performance can be improved, ensuring data transmission to destination nodes placed at a large distance from the WSN

Optimal Mission Planning of Autonomous Mobile Agents for Applications in Microgrids, Sensor Networks, and Military Reconnaissance

As technology advances, the use of collaborative autonomous mobile systems for various applications will become evermore prevalent. One interesting application of these multi-agent systems is for autonomous mobile microgrids. These systems will play an increasingly important role in applications such as military special operations for mobile ad-hoc power infrastructures and for intelligence, surveillance, and reconnaissance missions. In performing these operations with these autonomous energy assets, there is a crucial need to optimize their functionality according to their specific application and mission. Challenges arise in determining mission characteristics such as how each resource should operate, when, where, and for how long. This thesis explores solutions in determining optimal mission plans around the applications of autonomous mobile microgrids and resource scheduling with UGVs and UAVs. Optimal network connections, energy asset locations, and cabling trajectories are determined in the mobile microgrid application. The resource scheduling applications investigate the use of a UGV to recharge wireless sensors in a wireless sensor network. Optimal recharging of mobile distributed UAVs performing reconnaissance missions is also explored. With genetic algorithm solution approaches, the results show the proposed methods can provide reasonable a-priori mission plans, considering the applied constraints and objective functions in each application. The contributions of this thesis are: (1) The development and analysis of solution methodologies and mission simulators for a-priori mission plan development and testing, for applications in organizing and scheduling power delivery with mobile energy assets. Applying these methods results in (2) the development and analysis of reasonable a-priori mission plans for autonomous mobile microgrids/assets, in various scenarios. This work could be extended to include a more diverse set of heterogeneous agents and incorporate dynamic loads to provide power to

A Survey on Mobile Charging Techniques in Wireless Rechargeable Sensor Networks

The recent breakthrough in wireless power transfer (WPT) technology has empowered wireless rechargeable sensor networks (WRSNs) by facilitating stable and continuous energy supply to sensors through mobile chargers (MCs). A plethora of studies have been carried out over the last decade in this regard. However, no comprehensive survey exists to compile the state-of-the-art literature and provide insight into future research directions. To fill this gap, we put forward a detailed survey on mobile charging techniques (MCTs) in WRSNs. In particular, we first describe the network model, various WPT techniques with empirical models, system design issues and performance metrics concerning the MCTs. Next, we introduce an exhaustive taxonomy of the MCTs based on various design attributes and then review the literature by categorizing it into periodic and on-demand charging techniques. In addition, we compare the state-of-the-art MCTs in terms of objectives, constraints, solution approaches, charging options, design issues, performance metrics, evaluation methods, and limitations. Finally, we highlight some potential directions for future research

A Survey on Energy Optimization Techniques in UAV-Based Cellular Networks: From Conventional to Machine Learning Approaches

Wireless communication networks have been witnessing an unprecedented demand due to the increasing number of connected devices and emerging bandwidth-hungry applications. Albeit many competent technologies for capacity enhancement purposes, such as millimeter wave communications and network densification, there is still room and need for further capacity enhancement in wireless communication networks, especially for the cases of unusual people gatherings, such as sport competitions, musical concerts, etc. Unmanned aerial vehicles (UAVs) have been identified as one of the promising options to enhance the capacity due to their easy implementation, pop up fashion operation, and cost-effective nature. The main idea is to deploy base stations on UAVs and operate them as flying base stations, thereby bringing additional capacity to where it is needed. However, because the UAVs mostly have limited energy storage, their energy consumption must be optimized to increase flight time. In this survey, we investigate different energy optimization techniques with a top-level classification in terms of the optimization algorithm employed; conventional and machine learning (ML). Such classification helps understand the state of the art and the current trend in terms of methodology. In this regard, various optimization techniques are identified from the related literature, and they are presented under the above mentioned classes of employed optimization methods. In addition, for the purpose of completeness, we include a brief tutorial on the optimization methods and power supply and charging mechanisms of UAVs. Moreover, novel concepts, such as reflective intelligent surfaces and landing spot optimization, are also covered to capture the latest trend in the literature.Comment: 41 pages, 5 Figures, 6 Tables. Submitted to Open Journal of Communications Society (OJ-COMS