Related papers: Cooperative Multi-Agent Deep Reinforcement Learnin…
Over the past few years, the use of swarms of Unmanned Aerial Vehicles (UAVs) in monitoring and remote area surveillance applications has become widespread thanks to the price reduction and the increased capabilities of drones. The drones…
Integrating unmanned aerial vehicles (UAVs) into existing cellular networks encounters lots of challenges, among which one of the most striking concerns is how to achieve harmonious coexistence of aerial transceivers, inter alia, UAVs, and…
As artificial intelligence (AI)-enabled wireless communication systems continue their evolution, distributed learning has gained widespread attention for its ability to offer enhanced data privacy protection, improved resource utilization,…
This paper studies the allocation of shared resources between vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) links in vehicle-to-everything (V2X) communications. In existing algorithms, dynamic vehicular environments and…
The low-altitude Internet of Things (IoT), supported by unmanned aerial vehicles (UAVs), provides ground sensing networks with advanced real-time monitoring and data collection. To maximize data collection volume from distributed IoT nodes,…
Mobile edge computing (MEC) is a promising technique to improve the computational capacity of smart devices (SDs) in Internet of Things (IoT). However, the performance of MEC is restricted due to its fixed location and limited service…
The capability of UAVs for efficient autonomous navigation and obstacle avoidance in complex and unknown environments is critical for applications in agricultural irrigation, disaster relief and logistics. In this paper, we propose the DPRL…
A novel framework is proposed for the trajectory design of multiple unmanned aerial vehicles (UAVs) based on the prediction of users' mobility information. The problem of joint trajectory design and power control is formulated for…
Unmanned aerial vehicles (UAVs) can provide wireless access to terrestrial users, regardless of geographical constraints, and will be an important part of future communication systems. In this paper, a multi-user downlink dual-UAVs enabled…
In post-disaster scenarios, the rapid deployment of adequate communication infrastructure is essential to support disaster search, rescue, and recovery operations. To achieve this, uncrewed aerial vehicle (UAV) has emerged as a promising…
Unmanned aerial vehicles (UAVs) are expected to be an integral part of wireless networks, and determining collision-free trajectories for multiple UAVs while satisfying requirements of connectivity with ground base stations (GBSs) is a…
Maintaining the freshness of information in the Internet of Things (IoT) is a critical yet challenging problem. In this paper, we study cooperative data collection using multiple Unmanned Aerial Vehicles (UAVs) with the objective of…
This paper presents a novel deep reinforcement learning-based system for 3D mapless navigation for Unmanned Aerial Vehicles (UAVs). Instead of using a image-based sensing approach, we propose a simple learning system that uses only a few…
Reinforcement learning (RL) has been a promising essence in future 5G-beyond and 6G systems. Its main advantage lies in its robust model-free decision-making in complex and large-dimension wireless environments. However, most existing RL…
Cooperative communication using unmanned aerial vehicles (UAVs) is a promising technology for infrastructureless wireless networks. One of the key challenges in UAV based communications is the backhaul throughput. In this paper, we propose…
Unmanned Aerial Vehicles (UAVs) acting as Flying Access Points (FAPs) are being used to provide on-demand wireless connectivity in extreme scenarios. Despite ongoing research, the optimization of UAVs' positions according to dynamic users'…
A resource-constrained unmanned aerial vehicle (UAV) can be used as a flying LoRa gateway (GW) to move inside the target area for efficient data collection and LoRa resource management. In this work, we propose deep reinforcement learning…
Owing to the enhanced flexibility in deployment and decreasing costs of manufacturing, the demand for unmanned aerial vehicles (UAVs) is expected to soar in the upcoming years. In this paper, we explore a UAV aided search and rescue~(SAR)…
In this paper, a novel Three dimensional (3D) positioning framework of fluid antenna system (FAS)-enabled unmanned aerial vehicles (UAVs) is developed. In the proposed framework, a set of controlled UAVs cooperatively estimate the real-time…
Millimeter Wave (mmWave) is an important part of 5G new radio (NR), in which highly directional beams are adapted to compensate for the substantial propagation loss based on UE locations. However, the location information may have some…