Dynamic multiple access based on deep reinforcement learning for Internet of Things
X Liu, Z Li - Computer Communications, 2023 - Elsevier
With the development of wireless communication technology, the rational use of spectrum
resources utilizing efficient multiple access technology has become a research hotspot. The …
resources utilizing efficient multiple access technology has become a research hotspot. The …
Deep transfer reinforcement learning for resource allocation in hybrid multiple access systems
X Wang, Y Zhang, H Wu, T Liu, Y Xu - Physical Communication, 2022 - Elsevier
This paper proposes a resource allocation scheme for hybrid multiple access involving both
orthogonal multiple access and non-orthogonal multiple access (NOMA) techniques. The …
orthogonal multiple access and non-orthogonal multiple access (NOMA) techniques. The …
Multi-agent deep reinforcement learning for massive access in 5G and beyond ultra-dense NOMA system
With the rapid development of machine-type communications (MTC), the future
communication architecture needs to provide services for both human-type communications …
communication architecture needs to provide services for both human-type communications …
Effective radio resource allocation for IoT random access by using reinforcement learning
YW Chen, JZ You - Journal of Internet Technology, 2022 - jit.ndhu.edu.tw
Emerging intelligent and highly interactive services result in the mass deployment of internet
of things (IoT) devices. They are dominating wireless communication networks compared to …
of things (IoT) devices. They are dominating wireless communication networks compared to …
Dynamic user pairing and power allocation for NOMA with deep reinforcement learning
F Jiang, Z Gu, C Sun, R Ma - 2021 IEEE Wireless …, 2021 - ieeexplore.ieee.org
In this paper, we investigate the user pairing and power allocation scheme for multiple
cellular users (CUs) under the downlink non-orthogonal multiple access (NOMA) system. To …
cellular users (CUs) under the downlink non-orthogonal multiple access (NOMA) system. To …
A reinforcement learning approach to dynamic spectrum access in Internet-of-Things networks
H Cha, SL Kim - ICC 2019-2019 IEEE International Conference …, 2019 - ieeexplore.ieee.org
To support wireless communication traffic of Internet-of-Things (IoT) systems in terms of
massive connectivity, dynamic spectrum access (DSA) is important issue. This paper …
massive connectivity, dynamic spectrum access (DSA) is important issue. This paper …
An Energy-Efficient DL-Aided Massive Multiple Access Scheme for IoT Scenarios in Beyond 5G Networks
In view of the challenges foreseen in futuristic massive IoT (mIoT) scenarios, characterized
by a huge deployment of energy-constrained IoT devices, we propose an efficient next …
by a huge deployment of energy-constrained IoT devices, we propose an efficient next …
Dynamic spectrum access for internet-of-things based on federated deep reinforcement learning
The explosive growth of Internet-of-Things (IoT) applications such as smart cities and
Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating …
Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating …
A Deep Reinforcement Learning based Approach for NOMA-based Random Access Network with Truncated Channel Inversion Power Control
As a main use case of 5G and Beyond wireless network, the ever-increasing machine type
communications (MTC) devices pose critical challenges over MTC network in recent years. It …
communications (MTC) devices pose critical challenges over MTC network in recent years. It …
Dynamic spectrum access based on deep reinforcement learning for multiple access in cognitive radio
Z Li, X Liu, Z Ning - Physical Communication, 2022 - Elsevier
With the increasing shortage of spectrum resources, dynamic spectrum access (DSA)
technology is proposed to maximize the spectrum resources utilization. Traditional DSA …
technology is proposed to maximize the spectrum resources utilization. Traditional DSA …