ITU AI/ML in 5G Challenge: Radio Link Failure Prediction Challenge
Stable and high-quality internet connectivity is mandatory to 5G mobile networks, but once something unexpected happens, the influence of the defect is quite severing. The talk will describe the problem ITU-ML5G-PS-036, Using weather info for radio link failure (RLF) prediction. This problem is about how to predict radio link failure using weather information and network KPIs. Then, the dataset will be described together with the goals of the challenge. Participants are required to create a Machine Learning model to pinpoint the network status of failures and mis-operation using the provided data sets and evaluate the performance of the developed model.
Speakers, Panelists and Moderators
SALIH ERGUTFocus Group Vice-ChairmanTurkcell 5G R&DDr Salih Ergut has more than 15 years of experience in the telecommunication domain in academia and industry. He has worked for vendor and operator companies in the sector including Ericsson Wireless (San Diego, CA), Ericsson Silicon Valley, Aware (Boston, MA), Nextwave (San Diego, CA), Turk Telekom Group (Istanbul, Turkey) and is currently working at Turkcell 5G R&D team in Istanbul, Turkey. He received his BS in Electrical Engineering from Bilkent University (Ankara, Turkey), MS in Electrical & Computer Engineering from Northeastern University (Boston, MA), and PhD in Electrical & Computer Engineering from University of California San Diego (La Jolla, CA). His research interests include wireless communications, machine learning, big data technologies, 5G technologies, SDN, NFV, and IoT.