Deep Reinforcement Learning for AoI minimization in UAV-aided data collection for WSN and IoT: A survey
Deep reinforcement learning (DRL) has emerged as a promising technique for optimizing
the deployment of unmanned aerial vehicles (UAVs) for data collection in wireless sensor …
the deployment of unmanned aerial vehicles (UAVs) for data collection in wireless sensor …
An exploratory bibliometric analysis of the literature on the age of information-aware unmanned aerial vehicles aided communication
Real-time status updates require more frequent updates with fresh information. This study
investigates the applications and research potential of unmanned aerial vehicles (UAV) for …
investigates the applications and research potential of unmanned aerial vehicles (UAV) for …
Counter uav swarms: Challenges, considerations, and future directions in uav warfare
Modern advances in unmanned aerial vehicle (UAV) technology have widened the scope of
commercial and military applications. However, the increased dependency on wireless …
commercial and military applications. However, the increased dependency on wireless …
Intelligent Adaptive MIMO Transmission for Nonstationary Communication Environment: A Deep Reinforcement Learning Approach
X Lin, A Liu, C Han, X Liang, Y Sun… - IEEE Transactions on …, 2025 - ieeexplore.ieee.org
Multiple-input multiple-output (MIMO) technology can effectively improve transmission
throughput and reliability by utilizing spatial wireless resources, which has aroused …
throughput and reliability by utilizing spatial wireless resources, which has aroused …
On the mobility effect in UAV-mounted absorbing metasurfaces: A theoretical and experimental study
In this work, we focus on the theoretical modeling and experimental evaluation of absorbing
metasurfaces mounted on unmanned aerial vehicles (UAVs) as facilitators for secure …
metasurfaces mounted on unmanned aerial vehicles (UAVs) as facilitators for secure …
Fairness-aware computation offloading with trajectory optimization and phase-shift design in RIS-assisted multi-UAV MEC network
S Wang, X Song, T Song, Y Yang - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) are regarded as a promising solution for mobile-edge
computing (MEC) systems due to their flexibility and capability to provide computing services …
computing (MEC) systems due to their flexibility and capability to provide computing services …
Coverage strategy for small-cell uav-based networks in iot environment
In wireless communication, small cells are low-powered cellular base stations that can be
used to enhance the coverage and capacity of wireless networks in areas where traditional …
used to enhance the coverage and capacity of wireless networks in areas where traditional …
AoI and Energy-Aware Data Collection for IRS-Assisted UAV-IoT Networks Under Jamming
P Wang, K Liu, Y Ma, Q Gao - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
With the rapid popularity of unmanned aerial vehicle (UAV)-Internet of Things (IoT) networks,
timely and energy-efficient data collection is a critical issue. The strong line-of-sight (LoS) …
timely and energy-efficient data collection is a critical issue. The strong line-of-sight (LoS) …
Integrating Reconfigurable Intelligent Surface and Modified Aquila Optimisation for Enhancing Wireless Communication Capacity
This paper introduces a modified version of the Aquila Optimization Algorithm (AOA)
designed to maximize achievable rates in multiuser wireless communication systems …
designed to maximize achievable rates in multiuser wireless communication systems …
Timeliness of Information in 5G Non-Terrestrial Networks: A Survey
This paper explores the significance of the timeliness of information in the context of fifth
generation (5G) non-terrestrial networks (NTN). As 5G technology continues to evolve, its …
generation (5G) non-terrestrial networks (NTN). As 5G technology continues to evolve, its …