ITU AI/ML in 5G Challenge: Improving the capacity of IEEE 802.11 WLANs through Machine Learning
The talk is intended to present, describe and solve doubts concerning the problem statement “Improving the capacity of IEEE 802.11 WLANs through Machine Learning” (https://www.upf.edu/web/wnrg/ai_challenge) of the ITU AI/ML in 5G Challenge. The first part of the talk will be devoted to introducing IEEE 802.11 WLANs and the Channel Bonding (CB) problem. Then, the dataset will be described together with the goals of the challenge.
Speakers, Panelists and Moderators
FRANCESC WILHELMIFrancesc holds a BSc degree in Telematics Engineering from the Universitat Pompeu Fabra (2015) with a focus on Broadband and Wireless Communications. With the aim of applying new techniques for solving many well-known problems in communications, Francesc obtained his MSc degree in Intelligent and Interactive Systems also from the UPF in 2016. He is now a Ph.D. Student in the Wireless Networking Group (WN) of the Department of Information and Communication Technologies (DTIC) at the UPF. His Ph.D. thesis is mostly focused on spectral efficiency for high-density wireless networks, thus showing the potential of applying techniques such as Reinforcement Learning (RL) in decentralized scenarios. Francesc is also involved in some standardization activities held by the ITU-T. In particular, his an active collaborator of the Focus Group on Machine Learning for Future Networks including 5G (FG-ML5G). With regards to education, Francesc has been a teaching assistant in the “Networks”, “Wireless Multimedia Networks” and “Laboratory Networks” subjects at the UPF from 2015 to present.