Application of machine learning in wireless networks: Key techniques and open issues
As a key technique for enabling artificial intelligence, machine learning (ML) is capable of
solving complex problems without explicit programming. Motivated by its successful …
solving complex problems without explicit programming. Motivated by its successful …
Toward massive machine type communications in ultra-dense cellular IoT networks: Current issues and machine learning-assisted solutions
The ever-increasing number of resource-constrained machine-type communication (MTC)
devices is leading to the critical challenge of fulfilling diverse communication requirements …
devices is leading to the critical challenge of fulfilling diverse communication requirements …
Unsupervised machine learning for networking: Techniques, applications and research challenges
While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …
research, the bulk of such works has focused on supervised learning. Recently, there has …
[HTML][HTML] Knowledge-defined networking: Applications, challenges and future work
Future 6G wireless communication systems are expected to feature intelligence and
automation. Knowledge-defined networking (KDN) is an evolutionary step toward …
automation. Knowledge-defined networking (KDN) is an evolutionary step toward …
Dynamic femtocell gNB on/off strategies and seamless dual connectivity in 5G heterogeneous cellular networks
X Huang, S Tang, Q Zheng, D Zhang, Q Chen - IEEE Access, 2018 - ieeexplore.ieee.org
To meet the drastic growth of the mobile traffic, 5G network is designed to optimize the
transmission efficiency and provide higher quality of service (QoS). Small cell is considered …
transmission efficiency and provide higher quality of service (QoS). Small cell is considered …
High bandwidth green communication with vehicles by decentralized resource optimization in integrated access backhaul 5G networks
H Alghafari, MS Haghighi… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recently, moving networks, including mobile small cells (MSCs), have been introduced to
improve the QoS experienced by users inside public transport and connected vehicles …
improve the QoS experienced by users inside public transport and connected vehicles …
Machine-learning approach for user association and content placement in fog radio access networks
The joint user association and cache placement problem is challenging in fog radio access
networks (F-RANs) due to its difficulty to present the optimal solution with low complexity …
networks (F-RANs) due to its difficulty to present the optimal solution with low complexity …
Intelligent wireless networks: challenges and future research topics
M Abusubaih - Journal of Network and Systems Management, 2022 - Springer
Recently, artificial intelligence (AI) has become a primary tool of serving science and
humanity in all fields. This is due to the significant development in computing. The use of AI …
humanity in all fields. This is due to the significant development in computing. The use of AI …
Soft frequency reuse with allocation of resource plans based on machine learning in the networks with flying base stations
MS Hossain, Z Becvar - IEEE Access, 2021 - ieeexplore.ieee.org
Flying base stations (FlyBSs) enable ubiquitous communications in the next generation
mobile networks with a flexible topology. However, a deployment of the FlyBSs intensifies …
mobile networks with a flexible topology. However, a deployment of the FlyBSs intensifies …
Memory-based user-centric backhaul-aware user cell association scheme
Ultra-dense small cell networks represent a key future network solution that can help meet
the exponentially rising traffic requirements of modern wireless networks. Backhauling these …
the exponentially rising traffic requirements of modern wireless networks. Backhauling these …