A deep reinforcement learning based mechanism for cell outage compensation in massive IoT environments
As one of the key technologies of 5G, massive IoT environments provide the ubiquitous IoT
services. Compared with 4G, its structure is more complex, and it has a large number of …
services. Compared with 4G, its structure is more complex, and it has a large number of …
A deep reinforcement learning based mechanism for cell outage compensation in 5G UDN
Ultra Dense Networks (UDN) have become one of the key technologies for 5G wireless
communications, which can meet the requirements of high-traffic, high-density wireless …
communications, which can meet the requirements of high-traffic, high-density wireless …
QoE driven resource allocation in massive IoT: A deep reinforcement learning approach
J Zhao, S Xu, D Li - 2019 IEEE International Conference on …, 2019 - ieeexplore.ieee.org
Dense deployment of various Internet of Things (IoT) equipment in cellular will lead to a
sharp shortage of frequency resources. Consequently, how to make efficient utilization of …
sharp shortage of frequency resources. Consequently, how to make efficient utilization of …
A cell outage compensation mechanism based on IPSO for 5G ultra-dense small cell networks
To cope with the increment of mobile communication in 5G networks, Internet Service
Providers are planning to adopt base stations with less power and smaller coverage in a …
Providers are planning to adopt base stations with less power and smaller coverage in a …
Deep reinforcement learning aided cell outage compensation framework in 5G cloud radio access networks
As one of the key technologies of 5G, Cloud Radio Access Networks (C-RAN) with cloud
BBUs (Base Band Units) pool architecture and distributed RRHs (Remote Radio Heads) can …
BBUs (Base Band Units) pool architecture and distributed RRHs (Remote Radio Heads) can …
Sub-band assignment and power control for IoT cellular networks via deep learning
HW Kim, HJ Park, SH Chae - IEEE Access, 2022 - ieeexplore.ieee.org
As various Internet of things (IoT) communication services have recently received great
attention, the development of resource allocation scheme that can support the connection of …
attention, the development of resource allocation scheme that can support the connection of …
Optimal Radio Resource Allocation in Small Cells for a Massive IoT Network: An mMTC Perspective
The growing number of resource-restrained Machine-Type Communications (MTC) gadgets
such as IoT devices are generating challenges toward obtaining miscellaneous …
such as IoT devices are generating challenges toward obtaining miscellaneous …
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 …
A novel deep reinforcement learning algorithm for online antenna tuning
E Balevi, JG Andrews - 2019 IEEE Global Communications …, 2019 - ieeexplore.ieee.org
The interactions between the cells, most notably due to their coupled interference and the
large number of users, render the optimization of antenna parameters prohibitively complex …
large number of users, render the optimization of antenna parameters prohibitively complex …
Spatio-temporal degree of freedom: interference management in 5G Edge SON networks
J Hong, YH Cho, SK Kim, JH Na… - 2021 International …, 2021 - ieeexplore.ieee.org
According to Cisco's recent white paper, the usage of mobile data is exponentially
increasing by 2022, namely 330% enhancement compared to 2017. Therefore …
increasing by 2022, namely 330% enhancement compared to 2017. Therefore …