Unsupervised machine learning for networking: Techniques, applications and research challenges

M Usama, J Qadir, A Raza, H Arif, KLA Yau… - IEEE …, 2019 - ieeexplore.ieee.org
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 …

[PDF][PDF] Applications of artificial intelligence in machine learning: review and prospect

S Das, A Dey, A Pal, N Roy - International Journal of Computer …, 2015 - Citeseer
Machine learning is one of the most exciting recent technologies in Artificial Intelligence.
Learning algorithms in many applications that's we make use of daily. Every time a web …

Machine learning paradigms for next-generation wireless networks

C Jiang, H Zhang, Y Ren, Z Han… - IEEE Wireless …, 2016 - ieeexplore.ieee.org
Next-generation wireless networks are expected to support extremely high data rates and
radically new applications, which require a new wireless radio technology paradigm. The …

Priority-based reserved spectrum allocation by multi-agent through reinforcement learning in cognitive radio network

B Jaishanthi, EN Ganesh, D Sheela - Automatika: časopis za …, 2019 - hrcak.srce.hr
Sažetak Research in cognitive radio networks aims at maximized spectrum utilization by
giving access to increased users with the help of dynamic spectrum allocation policy. The …

Radio resource allocation techniques for efficient spectrum access in cognitive radio networks

GI Tsiropoulos, OA Dobre, MH Ahmed… - … Surveys & Tutorials, 2014 - ieeexplore.ieee.org
This paper provides an overview of cognitive radio (CR) networks, with focus on the recent
advances in resource allocation techniques and the CR networks architectural design. The …

Cognitive radio: survey on communication protocols, spectrum decision issues, and future research directions

J Marinho, E Monteiro - Wireless networks, 2012 - Springer
Currently, the radio spectrum is statically allocated and divided between licensed and
unlicensed frequencies. Due to this inflexible policy, some frequency bands are growing in …

Towards 6G in-X subnetworks with sub-millisecond communication cycles and extreme reliability

R Adeogun, G Berardinelli, PE Mogensen… - IEEE …, 2020 - ieeexplore.ieee.org
The continuous proliferation of applications requiring wireless connectivity will eventually
result in latency and reliability requirements beyond what is achievable with current …

Intelligent wireless communications enabled by cognitive radio and machine learning

X Zhou, M Sun, GY Li, BHF Juang - China Communications, 2018 - ieeexplore.ieee.org
The ability to intelligently utilize resources to meet the need of growing diversity in services
and user behavior marks the future of wireless communication systems. Intelligent wireless …

The virtual windtunnel

S Bryson, S JOHAN, L SCHLECHT… - … Review 1998: (In 2 …, 1998 - World Scientific
This paper describes the virtual windtunnel, a virtual reality-based, near-real-time interactive
system for CFD visualization. The virtual windtunnel supports several visualization …

A comprehensive survey on machine learning approaches for dynamic spectrum access in cognitive radio networks

A Kaur, K Kumar - Journal of Experimental & Theoretical Artificial …, 2022 - Taylor & Francis
Due to exponential growth in demand for radio spectrum for wireless communication
networking, the radio spectrum has become over-crowded. The fixed spectrum allocation …