Factor Graph-based Deep Reinforcement Learning for Path Selection Scheme in Full-duplex Wireless Multihop Networks

Z Cui, ATP Khun, Y Lim, Y Tan - 2023 International Wireless …, 2023 - ieeexplore.ieee.org
Wireless Multihop Network (WMN) is set of wirelessly connected nodes without an aid of
centralized infrastructure that can forward any message via relaying nodes by multihop …

[HTML][HTML] Factor graph-based deep reinforcement learning for path selection scheme in full-duplex wireless multihop networks

Z Cui, Y Lim, Y Tan - Ad Hoc Networks, 2024 - Elsevier
A wireless multihop network (WMN) is set of wirelessly connected nodes without an aid of
centralized infrastructure that can forward any packets via intermediate nodes by a multihop …

Reinforcement learning based inter-user-interference suppression in full-duplex networks

D Korpi, MA Uusitalo - 2021 IEEE 93rd Vehicular Technology …, 2021 - ieeexplore.ieee.org
In this work, we propose a reinforcement learning (RL) based solution for managing inter-
user-interference in wireless full-duplex networks. In particular, the RL algorithm is trained to …

Hierarchical reinforcement learning for AP duplex mode optimization in network-assisted full-duplex cell-free networks

X Sun, C Sun, J Li, D Wang, H Zhang… - IEEE Systems …, 2023 - ieeexplore.ieee.org
Network-assisted full-duplex (NAFD) cell-free (CF) networks use half-duplex access points
(APs) to enable the network-level in-band full-duplex. By dynamically allocating each AP to …

Joint routing and scheduling for transmission service in software-defined full-duplex wireless networks

Z Li, X Chen, L Li, X Wang - Peer-to-Peer Networking and Applications, 2019 - Springer
In recent years, full-duplex communication has been investigated in wireless networks to
improve the quality of transmission service. Most existing work focused on the physical layer …

A deep CNN-based relay selection in EH full-duplex IoT networks with short-packet communications

TV Nguyen, T Huynh-The, B An - ICC 2021-IEEE International …, 2021 - ieeexplore.ieee.org
In this paper, we propose an efficient deep convolutional neural network-based relay
selection (CNS) scheme to evaluate and improve the end-to-end throughput in energy …

Deep reinforcement learning for dynamic clustering and resource allocation in smart-duplex networks

D Wang, C Huang - 2022 IEEE Wireless Communications and …, 2022 - ieeexplore.ieee.org
This paper considers an ultra dense network (UDN) with smart-duplex (SD), which allows
the base stations (BSs) to flexibly switch between half-duplex (HD) and full-duplex (FD) …

Capacity analysis and link scheduling design in double-channel full-duplex wireless networks

L Li, Z Li, X Chen - 2016 IEEE Trustcom/BigDataSE/ISPA, 2016 - ieeexplore.ieee.org
Full-duplex communication has been proved as a realizable way to enhance the capacity of
wireless network. In this paper, we analyze the asymptotic capacity of full-duplex wireless …

Dynamic clustering and resource allocation using deep reinforcement learning for smart-duplex networks

D Wang, C Huang, H Zhang, S Jiang… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Ultra dense networks (UDNs) with smart-duplex (SD), which allows the base stations (BSs)
to flexibly switch between the half-duplex (HD) and full-duplex (FD), are expected to support …

Deep reinforcement learning for RIS-aided multiuser full-duplex secure communications with hardware impairments

Z Peng, Z Zhang, L Kong, C Pan, L Li… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
In this article, we investigate a reconfigurable intelligent surface (RIS)-aided multiuser full-
duplex secure communication system with hardware impairments at transceivers and RIS …