A decoupled learning strategy for massive access optimization in cellular IoT networks

N Jiang, Y Deng, A Nallanathan… - IEEE Journal on Selected …, 2020 - ieeexplore.ieee.org
Cellular-based networks are expected to offer connectivity for massive Internet of Things
(mIoT) systems. However, their Random Access CHannel (RACH) procedure suffers from …

Deep reinforcement learning-based access class barring for energy-efficient mMTC random access in LTE networks

ATH Bui, AT Pham - IEEE Access, 2020 - ieeexplore.ieee.org
Long-Term Evolution (LTE) networks are expected to be a key enabler for the massive
Machine-Type Communications (mMTC) service in the 5G context. As highly synchronized …

面向大规模物联网的随机接入: 现状, 挑战与机遇

范平志, 李里, 陈欢, 程高峰, 杨林杰, 汤小波 - 通信学报, 2021 - infocomm-journal.com
在传统通信系统中, 随机接入是终端与网络之间建立无线链路的必经过程, 只有在随机接入完成
之后, 终端与网络之间才能正常进行数据传输. 聚焦大规模节点物联网, 首先阐述了大规模物联网 …

Joint power allocation and blocklength assignment for reliability optimization in CA-enabled HetNets

L Yang, J Jia, J Chen, X Wang - Peer-to-Peer Networking and Applications, 2024 - Springer
Heterogeneous cellular networks (HetNets) are widely recognized as representing the future
development trend of networks and provide architectural support for the emergence of many …

UAV aided Metaverse over Wireless Communications: A Reinforcement Learning Approach

P Si, W Yu, J Zhao, KY Lam, Q Yang - arXiv preprint arXiv:2301.01474, 2023 - arxiv.org
Metaverse is expected to create a virtual world closely connected with reality to provide
users with immersive experience with the support of 5G high data rate communication …

Pricing-based deep reinforcement learning for live video streaming with joint user association and resource management in mobile edge computing

PY Chou, WY Chen, CY Wang… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) is a promising technique in the 5G Era to improve the
Quality of Experience (QoE) for online video streaming due to its ability to reduce the …

Access delay optimization of double-contention random access scheme in machine-to-machine communications

C Zhang, X Sun, W Xia, R Huang… - IEEE …, 2023 - ieeexplore.ieee.org
Machine learning-based random access schemes have gained significant attention in recent
years. However, optimizing the access delay of such schemes remains a challenge. In this …

[HTML][HTML] Energy-efficient power control strategy of the delay tolerable service based on the reinforcement learning

M Bai, R Zhu, J Guo, F Wang, H Zhu, Y Zhang - Computer Communications, 2023 - Elsevier
In recent years, the rapid development of Internet technology and its applications has led to
an exponential growth in the number of Internet users and wireless terminal devices …

Graph neural network based interference estimation for device-to-device wireless communications

H Jiang, L Li, Z Wang, H He - 2021 International Joint …, 2021 - ieeexplore.ieee.org
This paper concerns interference estimation problem for device-to-device (D2D)
communication networks. In the considered system, D2D users share common spectrum …

Hierarchical beamforming in random access channels

A Agustin, J Vidal… - 2021 IEEE Global …, 2021 - ieeexplore.ieee.org
Managing a massive number of terminals in a contention-based multiple access is
challenging due to its intrinsic limited efficiency. For example, in the random access channel …