A NOMA-Based Q-Learning Random Access Method for Machine Type Communications
Machine Type Communications (MTC) is a main use case of 5G and beyond wireless
networks. Moreover, due to the ultra-dense nature of massive MTC networks, Random …
networks. Moreover, due to the ultra-dense nature of massive MTC networks, Random …
D2d assisted q-learning random access for noma-based mtc networks
Machine-type communications (MTC) should account for half the connections to the internet
by 2030. The use case massive MTC (mMTC) allows for applications to connect a massive …
by 2030. The use case massive MTC (mMTC) allows for applications to connect a massive …
Distributed Q-learning aided uplink grant-free NOMA for massive machine-type communications
The explosive growth of machine-type communications (MTC) devices poses critical
challenges to the existing cellular networks. Therefore, how to support massive MTC devices …
challenges to the existing cellular networks. Therefore, how to support massive MTC devices …
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 …
Efficient resource allocation in fast-uplink grant for machine-type communications with NOMA
M El Tanab, W Hamouda - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Efficient uplink access is a keystone for the successful deployment of machine-type
communication (MTC) that enables the promising Internet of Things (IoT). In this article, we …
communication (MTC) that enables the promising Internet of Things (IoT). In this article, we …
Heterogeneous machine-type communications in cellular networks: Random access optimization by deep reinforcement learning
Z Chen, DB Smith - 2018 IEEE International Conference on …, 2018 - ieeexplore.ieee.org
One of the significant challenges for managing machine-to-machine (M2M) communication
in cellular networks, such as LTE-A, is the overload of the radio access network due to very …
in cellular networks, such as LTE-A, is the overload of the radio access network due to very …
A decoupled learning strategy for massive access optimization in cellular IoT networks
Cellular-based networks are expected to offer connectivity for massive Internet of Things
(mIoT) systems. However, their Random Access CHannel (RACH) procedure suffers from …
(mIoT) systems. However, their Random Access CHannel (RACH) procedure suffers from …
Learning automata-based access class barring scheme for massive random access in machine-to-machine communications
C Di, B Zhang, Q Liang, S Li… - IEEE Internet of Things …, 2018 - ieeexplore.ieee.org
The machine-to-machine (M2M) communications, which achieve the implementation of
Internet of Things (IoT), can be carried over wireless cellular networks. The massive random …
Internet of Things (IoT), can be carried over wireless cellular networks. The massive random …
Prior information aided deep learning method for grant-free NOMA in mMTC
In massive machine-type communications (mMTC), the conflict between millions of potential
access devices and limited channel freedom leads to a sharp decrease in spectrum …
access devices and limited channel freedom leads to a sharp decrease in spectrum …
Active user detection and channel estimation for massive machine-type communication: Deep learning approach
Recently, massive machine-type communications (mMTCs) have become one of key use
cases for 5G. In order to support massive users transmitting small data packets at low rates …
cases for 5G. In order to support massive users transmitting small data packets at low rates …