DDPG-based aerial secure data collection

H Lei, H Ran, IS Ansari, KH Park, G Pan… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
As air-to-ground links tend to exhibit a high probability of being line-of-sight (LoS),
unmanned aerial vehicles (UAVs) are widely used to improve the performance of wireless …

HiMAQ: Hierarchical multi-agent Q-learning-based throughput and fairness improvement for UAV-Aided IoT networks

E Kim, J Kim, JH Kim, H Lee - Journal of Network and Computer …, 2024 - Elsevier
Recently, various types of Internet of Things (IoT) services have become wide spread, and
new types of IoT devices are emerging. However, the significant number of high-rise …

Caching-at-STARS: The next generation edge caching

Z Hu, R Zhong, C Fang, Y Liu - IEEE Transactions on Wireless …, 2024 - ieeexplore.ieee.org
A simultaneously transmitting and reflecting surface (STARS) enabled edge caching system
is proposed for reducing backhaul traffic and ensuring the quality of service. A novel …

DRL-Based Resource Allocation and Trajectory Planning for NOMA-Enabled Multi-UAV Collaborative Caching 6 G Network

P Qin, Y Fu, J Zhang, S Geng, J Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Aerial platform-based network has been invoked as an appealing assistance for terrestrial
cellular networks. Caching at edge UAVs is an effective emerging solution for relieving the …

Safety constrained trajectory optimization for completion time minimization for uav communications

T Wang, W Du, C Jiang, Y Li… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
In recent years, unmanned aerial vehicles (UAVs) are considered to be integrated into
wireless communication systems because of their tremendous advantages in mobility, cost …

[HTML][HTML] Spectrum-efficient user grouping and resource allocation based on deep reinforcement learning for mmWave massive MIMO-NOMA systems

M Wang, X Liu, F Wang, Y Liu, T Qiu, M Jin - Scientific Reports, 2024 - nature.com
Millimeter-wave (mmWave) massive multiple-input multiple-output non-orthogonal multiple
access (MIMO-NOMA) is proven to be a primary technique for sixth-generation (6G) wireless …

Efficient Communications in Multi-Agent Reinforcement Learning for Mobile Applications

Z Lv, L Xiao, Y Du, Y Zhu, S Han… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The environment observations and learning experiences shared by the cooperative learning
agents accelerate multi-agent reinforcement learning (MARL) with partial observations for …

Resource management for sum-rate maximization in SCMA-assisted UAV system

S Chaturvedi, VA Bohara, Z Liu, A Srivastava… - Vehicular …, 2024 - Elsevier
This work presents a resource management framework for optimizing the sum-rate in a
sparse code multiple access (SCMA)-assisted UAV downlink system. We formulate two …

A Survey on Intelligent Internet of Things: Applications, Security, Privacy, and Future Directions

O Aouedi, TH Vu, A Sacco, DC Nguyen… - arXiv preprint arXiv …, 2024 - arxiv.org
The rapid advances in the Internet of Things (IoT) have promoted a revolution in
communication technology and offered various customer services. Artificial intelligence (AI) …

Joint UAV trajectory and communication design with heterogeneous multi-agent reinforcement learning

X Zhou, J Xiong, H Zhao, X Liu, B Ren, X Zhang… - Science China …, 2024 - Springer
Unmanned aerial vehicles (UAVs) are recognized as effective means for delivering
emergency communication services when terrestrial infrastructures are unavailable. This …