Applications of multi-agent deep reinforcement learning: Models and algorithms
Recent advancements in deep reinforcement learning (DRL) have led to its application in
multi-agent scenarios to solve complex real-world problems, such as network resource …
multi-agent scenarios to solve complex real-world problems, such as network resource …
A Bayesian framework for digital twin-based control, monitoring, and data collection in wireless systems
Commonly adopted in the manufacturing and aerospace sectors, digital twin (DT) platforms
are increasingly seen as a promising paradigm to control, monitor, and analyze software …
are increasingly seen as a promising paradigm to control, monitor, and analyze software …
Survey of reinforcement-learning-based MAC protocols for wireless ad hoc networks with a MAC reference model
Z Zheng, S Jiang, R Feng, L Ge, C Gu - Entropy, 2023 - mdpi.com
In this paper, we conduct a survey of the literature about reinforcement learning (RL)-based
medium access control (MAC) protocols. As the scale of the wireless ad hoc network …
medium access control (MAC) protocols. As the scale of the wireless ad hoc network …
[HTML][HTML] Deep Reinforcement Learning for QoS provisioning at the MAC layer: A Survey
Abstract Quality of Service (QoS) provisioning is based on various network management
techniques including resource management and medium access control (MAC). Various …
techniques including resource management and medium access control (MAC). Various …
Multi-channel opportunistic access for heterogeneous networks based on deep reinforcement learning
This paper investigates a new medium access control (MAC) protocol for multi-channel
heterogeneous networks (HetNets) based on deep reinforcement learning (DRL), referred to …
heterogeneous networks (HetNets) based on deep reinforcement learning (DRL), referred to …
Recent Advances in Data-driven Intelligent Control for Wireless Communication: A Comprehensive Survey
W Huo, H Yang, N Yang, Z Yang, J Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
The advent of next-generation wireless communication systems heralds an era
characterized by high data rates, low latency, massive connectivity, and superior energy …
characterized by high data rates, low latency, massive connectivity, and superior energy …
Machine Learning for Spectrum Sharing: A Survey
FRV Guimarães, JMB da Silva Jr… - … and Trends® in …, 2024 - nowpublishers.com
Abstract The 5th generation (5G) of wireless systems is being deployed with the aim to
provide many sets of wireless communication services, such as low data rates for a massive …
provide many sets of wireless communication services, such as low data rates for a massive …
Digital twin-based multiple access optimization and monitoring via model-driven bayesian learning
Commonly adopted in the manufacturing and aerospace sectors, digital twin (DT) platforms
are increasingly seen as a promising paradigm to control and monitor software …
are increasingly seen as a promising paradigm to control and monitor software …
Adversarial jamming attacks and defense strategies via adaptive deep reinforcement learning
As the applications of deep reinforcement learning (DRL) in wireless communications grow,
sensitivity of DRL based wireless communication strategies against adversarial attacks has …
sensitivity of DRL based wireless communication strategies against adversarial attacks has …
A Semantic-Aware Multiple Access Scheme for Distributed, Dynamic 6G-Based Applications
The emergence of the semantic-aware paradigm presents opportunities for innovative
services, especially in the context of 6G-based applications. Although significant progress …
services, especially in the context of 6G-based applications. Although significant progress …