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Machine learning enabled multi-radio access technology selection in 5G networks
Nurudeen Salau,
Muhammad Shakir
School of Computing, Engineering and Physical Sciences
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Keyphrases
World Population
100%
Mobile Users
100%
Machine Learning
100%
Subscriber
100%
Bandwidth Limitation
100%
Geographical Location
100%
Pedestrian
100%
5G Networks
100%
Machine Learning Approach
100%
Multi-RAT
100%
Geographic Mobility
100%
Radio Access Technology Selection
100%
Computer Science
Quality of Service
100%
Geographical Location
100%
Bandwidth Requirement
100%
Machine Learning Approach
100%
5G Mobile Communication
100%
Access Technology
100%
World Population
100%
Machine Learning
100%
Learning System
100%
Engineering
Radio Access Technology
100%
Learning System
100%
5G Mobile Communication
100%
Learning Approach
50%
Mobile User
50%
Bandwidth Requirement
50%
Geographical Location
50%
Quality of Service
50%
Chemical Engineering
Learning System
100%