Energy efficient joint computation offloading and service caching for mobile edge computing: A deep reinforcement learning approach
Mobile Edge Computing (MEC) meets the delay requirements of emerging applications and
reduces energy consumption by pushing cloud functions to the edge of the networks …
reduces energy consumption by pushing cloud functions to the edge of the networks …
Resource scheduling for UAVs-aided D2D networks: A multi-objective optimization approach
Unmanned aerial vehicles (UAVs)-aided device-to-device (D2D) networks have attracted
great interests with the development of 5G/6G communications, while there are several …
great interests with the development of 5G/6G communications, while there are several …
A hybrid improved manta ray foraging optimization with Tabu search algorithm for solving the UAV placement problem in smart cities
The concept of smart cities is to enhance the life quality of residents and provide efficient
services by integrating advanced information and communication technologies, autonomous …
services by integrating advanced information and communication technologies, autonomous …
Optimization of Placement and Resource Allocation in UAV-aided Multi-hop Wireless Networks
This article investigates the performance of cellular networks assisted by unmanned aerial
vehicles (UAVs) acting as flying base stations (FlyBSs). We focus on a scenario with …
vehicles (UAVs) acting as flying base stations (FlyBSs). We focus on a scenario with …
Analysis of Fluctuating Antenna Beamwidth in UAV-Assisted Cellular Networks
This paper investigates a cellular network assisted by unmanned aerial vehicles (UAVs) in
the presence of a fluctuating 3-dimensional (3D) antenna beamwidth. The primary objective …
the presence of a fluctuating 3-dimensional (3D) antenna beamwidth. The primary objective …
Dense Multi-Agent Reinforcement Learning Aided Multi-UAV Information Coverage for Vehicular Networks
With the rapid development of wireless communication networks, UAVs serving as base
stations are increasingly being applied in various scenarios which not only include edge …
stations are increasingly being applied in various scenarios which not only include edge …
Optimizing the Deployment of UAV for Mesh Access Network Coverage
F Senel, N Aschenbruck - 2023 IEEE 48th Conference on Local …, 2023 - ieeexplore.ieee.org
This paper proposes an optimal deployment strategy for Unmanned Aerial Vehicles (UAVs)
to create a wireless mesh network above ground users in an area without internet …
to create a wireless mesh network above ground users in an area without internet …
Managing sets of flying base stations using energy efficient 3D trajectory planning in cellular networks
MJ Sobouti, AH Mohajerzadeh, SAH Seno… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) in cellular networks have garnered considerable interest.
One of their applications is as flying base stations (FBSs), which can increase coverage and …
One of their applications is as flying base stations (FBSs), which can increase coverage and …
Computing over the Sky: Joint UAV Trajectory and Task Offloading Scheme Based on Optimization-Embedding Multi-Agent Deep Reinforcement Learning
X Li, X Du, N Zhao, X Wang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) has emerged to
support computation-intensive tasks in 6G systems. Since the battery capacity of a UAV is …
support computation-intensive tasks in 6G systems. Since the battery capacity of a UAV is …
UAV-Assisted Fair Communication for Mobile Networks: A Multi-Agent Deep Reinforcement Learning Approach
Y Zhou, Z Jin, H Shi, Z Wang, N Lu, F Liu - Remote Sensing, 2022 - mdpi.com
Unmanned Aerial Vehicles (UAVs) can be employed as low-altitude aerial base stations
(UAV-BSs) to provide communication services for ground users (GUs). However, most …
(UAV-BSs) to provide communication services for ground users (GUs). However, most …