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Data privacy is a major concern in industries such as healthcare or finance. The requirement to safeguard privacy is essential to prevent data breaches and misuse, which can have severe consequences for individuals and organisations.…
This study focuses on MEC-enhanced, vehicle-based crowdsensing systems that rely on devices installed on automobiles. We investigate an opportunistic communication paradigm in which devices can transmit measured data directly to a…
Flying Networks (FNs) have emerged as a promising solution to provide on-demand wireless connectivity when network coverage is insufficient or the communications infrastructure is compromised, such as in disaster management scenarios.…
Low altitude uncrewed aerial vehicles (UAVs) are expected to facilitate the development of aerial-ground integrated intelligent transportation systems and unlocking the potential of the emerging low-altitude economy. However, several…
In this work, performance of a multi-antenna multiuser unmanned aerial vehicle (UAV) assisted terrestrial-satellite communication system over mixed free space optics (FSO)/ radio frequency (RF) channels is analyzed. Downlink transmission…
Fluid antenna systems (FAS) have emerged as a revolutionary technology offering enhanced spatial diversity within a compact form factor. Concurrently, unmanned aerial vehicles (UAVs) are integral to future networks, necessitating channel…
Fog computing is an emerging distributed computing model for the Internet of Things (IoT). It extends computing and caching functions to the edge of wireless networks. Uncrewed Aerial Vehicles (UAVs) provide adequate support for fog…
In complex Unmanned Aerial Vehicle (UAV) networks, UAVs can establish dynamic and heterogeneous links with one another for various purposes, such as communication coverage, collective sensing, and task collaboration. These interactions give…
We study the problem of learning a function that maps context observations (input) to parameters of a submodular function (output). Our motivating case study is a specific type of vehicle routing problem, in which a team of Unmanned Ground…
Unmanned aerial vehicle (UAV)-based base stations offer a promising solution in emergencies where the rapid deployment of cutting-edge networks is crucial for maximizing life-saving potential. Optimizing the strategic positioning of these…
Several adaptation techniques have been investigated to optimize fuzzy inference systems. Neural network learning algorithms have been used to determine the parameters of fuzzy inference system. Such models are often called as integrated…
Unmanned aerial vehicles (UAVs) are playing an increasingly pivotal role in modern communication networks,offering flexibility and enhanced coverage for a variety of applica-tions. However, UAV networks pose significant challenges due to…
Unmanned aerial vehicles (UAVs) fill coverage holes as wireless relays during emergency situations. Fixed-wing UAVs offer longer flight duration and larger coverage in such situations than rotary-wing counterparts. Maximizing the…
Unmanned aerial vehicle (UAV)-based networks and Internet of Things (IoT) are being considered as integral components of current and next-generation wireless networks. In particular, UAVs can provide IoT devices with seamless connectivity…
Co-design optimisation of autonomous systems has emerged as a powerful alternative to sequential approaches by jointly optimising physical design and control strategies. However, existing frameworks often neglect the robustness required for…
In this paper, we propose a new resource allocation framework for unmanned aerial vehicle (UAV) assisted multicast wireless networks in which the network users according to their request are divided into several multicast groups. We adopt…
The application of intelligent decision-making in unmanned aerial vehicle (UAV) is increasing, and with the development of UAV 1v1 pursuit-evasion game, multi-UAV cooperative game has emerged as a new challenge. This paper proposes a deep…
The deployment flexibility and maneuverability of Unmanned Aerial Vehicles (UAVs) increased their adoption in various applications, such as wildfire tracking, border monitoring, etc. In many critical applications, UAVs capture images and…
Federated learning (FL) is an effective paradigm for enhancing the learning capability of edge devices while preserving data privacy. In geographically dispersed FL systems, such as sensor networks in remote areas, unmanned aerial vehicles…
Unmanned Aerial Vehicles (UAVs) are becoming increasingly useful for tasks which require the acquisition of data over large areas. The coverage problem, i.e., the problem of periodically visiting all subregions of an area at a desired…