Intelligent massive traffic handling scheme in 5G bottleneck backhaul networks
With the widespread deployment of the fifth-generation (5G) communication networks,
various real-time applications are rapidly increasing and generating massive traffic on …
various real-time applications are rapidly increasing and generating massive traffic on …
A deep-learning-based radio resource assignment technique for 5G ultra dense networks
Recently, deep learning has emerged as a state-of-the-art machine learning technique with
promising potential to drive significant breakthroughs in a wide range of research areas. The …
promising potential to drive significant breakthroughs in a wide range of research areas. The …
Traffic‐aware overload control scheme in 5G ultra‐dense M2M networks
Due to a huge number of M2M devices expected to access the network simultaneously,
congestion and overload of networks are the core challenges to the 5G ultra‐dense M2M …
congestion and overload of networks are the core challenges to the 5G ultra‐dense M2M …
ML-based traffic steering for heterogeneous ultra-dense beyond-5G networks
As networks become denser and more heterogeneous different paths can be considered in
order to reach each multi-homed UE, offering optimal performance. 5G and beyond …
order to reach each multi-homed UE, offering optimal performance. 5G and beyond …
Access and radio resource management for IAB networks using deep reinforcement learning
MM Sande, MC Hlophe, BT Maharaj - IEEE Access, 2021 - ieeexplore.ieee.org
Congestion in dense traffic networks is a prominent obstacle towards realizing the
performance requirements of 5G new radio. Since traditional adaptive traffic signal control …
performance requirements of 5G new radio. Since traditional adaptive traffic signal control …
[PDF][PDF] Intelligent Real-Time IoT Traffic Steering in 5G Edge Networks.
In the Next Generation Radio Networks (NGRN), there will be extreme massive connectivity
with the Heterogeneous Internet of Things (HetIoT) devices. The millimeter-Wave (mmWave) …
with the Heterogeneous Internet of Things (HetIoT) devices. The millimeter-Wave (mmWave) …
Deep reinforcement learning-based joint scheduling of eMBB and URLLC in 5G networks
J Li, X Zhang - IEEE Wireless Communications Letters, 2020 - ieeexplore.ieee.org
To satisfy tight latency constraints, ultra-reliable low latency communications (URLLC) traffic
is scheduled by overlapping the on-going enhanced mobile broad band (eMBB) …
is scheduled by overlapping the on-going enhanced mobile broad band (eMBB) …
Intelligent traffic adaptive resource allocation for edge computing-based 5G networks
The popularity of smart mobile devices has led to a tremendous increase in mobile traffic,
which has put a considerable strain on the fifth generation of mobile communication …
which has put a considerable strain on the fifth generation of mobile communication …
Performance analysis of support vector machine learning based carrier aggregation resource scheduling in 5g mobile communication
S Mathur, Y Chaba, A Noliya - Procedia Computer Science, 2023 - Elsevier
The 5G cellular system will enable heterogeneous networks that incorporate 5G, 4G, Wi-Fi,
and other telecommunication connectivity. This will result in huge changes in existing …
and other telecommunication connectivity. This will result in huge changes in existing …
Efficient and reliable hybrid deep learning-enabled model for congestion control in 5G/6G networks
Future generation networks such as millimeter-wave LAN, broadband wireless access
systems, and 5th or 6th generation (5G/6G) networks demand more security, low latency …
systems, and 5th or 6th generation (5G/6G) networks demand more security, low latency …