PROGRAMME
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The Grand Challenge Finale Schedule
Online, 15-17 December 2020
Contact: ai5gchallenge@itu.int
Note: Registration for
Tues 15 Dec and Wed. 16 Dec is different from
Thurs. 17 Dec
Day 1 - Tuesday, 15 December 2020 (Time zone - CET) Watch Video Recording (15 December event) 11:30-12:00
| Join session to test connection
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12:00-12:15
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Opening
Ceremony
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Welcome remarks: Reinhard Scholl, Deputy Director, Telecommunication Standardization Bureau, ITU
| | 12:15-12:30 |
Problem Statement – 5G+AI+AR
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PS-001.1 5Gn View remote collaboration Project [Presentation] [GitHub Repo]
5Gfan: Jiawang Liu and Jiaping Jiang, CITC of China Unicom, China
| 12:30-13:15
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Problem Statement – Analysis on route information failure in IP core networks by NFV-based test environment (KDDI, Japan).
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PS-032.2 Analysis on route information failure in IP core networks by NFV-based test environment [Presentation] [GitHub Repo]
UT-NakaoLab-AI: Fei Xia, Aerman Tuerxun, Jiaxing Lu, and Ping Du, University of Tokyo, Japan
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PS-032.1 On Failure Classification Based on GNN in IP Core Networks by NFV-Based Test Environment [Presentation] [GitHub Repo]
naist-lsmI: Takanori Hara, and Kentaro Fujita, Nara Institute of Science and Technology, Japan
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PS-032.3 Pre-training and fine-tuning approach for detecting route information failures in IP core networks [Presentation] [GitHub Repo]
mlab: Ryoma Kondo, Takashi Ubukata, Kentaro Matsuura, and Hirofumi Ohzeki, University of Tokyo, Japan
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13:15-13:30 | Problem Statement – Fault Localization of Loop Network Devices based on MEC Platform
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PS-002.1 Fault Localization of Loop Network Devices based on MEC Platform [Presentation] [GitHub Repo]
国创矩阵 (GuoChuang ChapterIX): Zhang Qi and Lin Xueqin, GUOCHUANG SOFTWARE CO., LTD., China
| 13:30-14:00
| Problem Statement – Network topology optimization
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PS-007.1
AI-Based Network Topology Optimization [Presentation] [Report]
小智 (Weeny Wit): Han Zengfu, Wang Zhiguo, Zhang Yiwei, Wu Desheng, Li Sicong, China Mobile Shandong, China -
PS-007.2 Applying Machine Learning in Network Topology Optimization [Presentation] [Report]
No Boundaries: Gang Zhouwei, Rao Qianyin, Feng Zezhong, Xi Lin, Guo Lin, China Mobile Guizhou, China
| 14:00-14:15
| Coffee break
| | 14:15-14:30 |
Problem Statement – Energy-Saving Prediction of Base Station Cells in Mobile Communication Network
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PS-005.1 Presentation Title [Presentation] [GitHub Repo]
浑水摸鱼 (Cresting): Wei Jiang, Shiyi Zhu, Xu Xu, AsiaInfo Technologies Limited, China
| 14:30-14:45
| Problem Statement – Out of Service(OOS) Alarm Prediction of 4/5G Network Base Station
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PS-008.1 Out of Service(OOS) Alarm Prediction [Presentation] [Report]
黑白双煞 (NKU-Excavator): Zhou Chao, Zheng Tianyu, Jiang Meijun, Nankai university, China
| 14:45-15:00
| Problem Statement – Demonstration of MLFO capabilities via reference implementations
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PS-024.1 MLFO Demonstration using Reference Implementation [Presentation] [GitHub Repo]
Abhishek Dandekar, TU Berlin, Germany
| 15:00-15:45
| Problem Statement – ML5G-PHY -Beam-Selection: Machine Learning Applied to the Physical Layer of Millimeter-Wave MIMO Systems (UFPA, Brazil)
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PS-012.2 NN-based mmWave Beam Selection utilizing LIDAR Data [Presentation] [GitHub Repo]
Imperial_IPC1: Mahdi Boloursaz Mashhadi, Tze-Yang Tung, Mikolaj Jankowski, Szymon Kobus, Imperial College London, United Kingdom
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PS-012.3 Deep Learning on Multimodal Sensor Data for Fast mmWave Beam Selection [Presentation] [GitHub Repo]
NU Huskies: Batool Salehihikouei, Debashri Roy, Guillem Reus Muns, Zifeng Wang, Tong Jian, Northeastern University, US
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PS-012.1 AI-Aided mmWave Beam Selection for Vehicular Communication [Presentation] [GitHub Repo]
BeamSoup: Zecchin Matteo, Eurecom, France
| 15:45-16:30
| Problem Statement – Improving the capacity of IEEE 802.11 WLANs through Machine Learning (UPF, Spain)
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PS-013.2 Multi-Layer Perceptron for OBSS throughput prediction [Presentation] [GitHub Repo]
Ramon Vallès, Universitat Pompeu Fabra, Spain
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PS-013.3 A Graph Neural Network approach for throughput prediction in next-generation WLANs [Presentation] [GitHub Repo]
ATARI: Paola Soto, David Goez, Miguel Camelo, Natalia Gaviria, University of Antwerp (Belgium) and Universidad de Antioquia (Colombia)
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PS-013.1 Dynamic Channel Bonding with Machine Learning [Presentation] [GitHub Repo]
STC_2: Mohammad Abid, Ayman M. Aloshan, Faisal Alomar, Mohammad Alfaifi, Abdulrahman Algunayyah, Khaled M. Sahari, Saudi Telecom Company, Saudi Arabia
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Day 2 - Wednesday, 16 December 2020 (Time zone - CET)Watch Video Recording (16 December event)
11:30-12:00
| Join session to test connection
| 12:00-12:15
| Problem Statement – 5G+AI (Smart Transportation) - (JNU, India)
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PS-019.1 Automated defect identification by AI video/image analytics with 5G- enabled remote road fixing vehicle [Presentation] [GitHub Repo]
STC: Atheer K. Alsaif, Nora M. Almuhanna, Abdulrahman Alromaih, Abdullah O. Alwashmi, Saudi Telecom Company, Saudi Arabia
| 12:15-13:00
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Problem Statement – Network State Estimation by Analyz-ing Raw Video Data (NEC, Japan)
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PS-031.1 Challenge for estimation of bandwidth and loss rate by focusing on the degradation characteristics of raw video data [Presentation] [GitHub Repo]
JOJO: Yuusuke Hashimoto, Yuya Seki, Daishi Kondo, Osaka Prefecture University, Japan
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PS-031.2 A Lightweight deep learning model for network state estimation using raw video data’ [Presentation] [GitHub Repo]
KCGI: Yimeng Sun, Badr Mochizuki, Kyoto College of Graduate Studies for Informatics, Japan
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PS-031.3 Network State Estimation by Analyzing Raw Video Data [Presentation] [GitHub Repo]
HENOKO KING: Fuyuki Higa, Gen Utidomari, Ryuma Kinjyo, Nao Uehara, National Institute of Technology, Okinawa College, Japan
| | 13:00-13:30 |
Problem Statement – Compression of Deep Learning models (ZTE)
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PS-018.1 End-Edge Cooperative Inference of Deep Learning Model Based on DNN Partition [Presentation] [GitHub Repo]
AI-Maglev: Yuwei Wang, Sheng Sun, Institute of Computing Technology Chinese Academy of Sciences, China
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PS-018.2 Multi-Context based Knowledge Distillation [Presentation] [GitHub Repo]
GAN Torrents: Satheesh Kumar Perepu,Saravanan Mohan, Vidya G, Thrivikram G L, Sethuraman T V, Ericsson Research India
| | 13:30-13:45 |
Problem Statement – Privacy Preserving AI/ML in 5G net-works for healthcare applications (C-DOT, India)
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PS-022.1 Dopamine: Differentially Private Secure Federated Learning on Medical Data [Presentation] [GitHub Repo]
I******L diagnostics: Mohammad Malekzadeh, Mehmet Emre Ozfatura,Kunal Katarya, Mital Nitish, Burak Hasircioglu, Imperial College London, United Kingdom
| 13:45-14:00
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Problem Statement – Shared Experience Using 5G+AI (3D Augmented + Virtual Reality) - (Hike, India)
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PS-023.1 Shared Experience Using 5G+AI (3D Augmented + Virtual Reality) [Presentation] [GitHub Repo]
Nitish Kumar Singh, Easyrewardz India, India
| 14:00-14:15
| Coffee break
| 14:15-15:00
| Problem Statement – Graph Neural Networking Challenge 2020 (BNN-UPC, Spain)
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PS-014.1 Graph Neural Networks for Physical Networks Modeling [Presentation] [GitHub Repo]
Steredeg: Loïck Bonniot, Christoph Neumann, François Schnitzler, François Taiani, InterDigital; Inria/Irisa
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PS-014.3 Hyperparameter Tuning for the RouteNet Modela [Presentation] [GitHub Repo]
Gradient Ascent: Nick Vincent Hainke, Stefan Venz, Johannes Wegener, Henrike Wissing, Fraunhofer HHI, Germany
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PS-014.2 A RouteNet Modification for Estimating Delays in Networks with Scheduling [Presentation] [GitHub Repo]
Salzburg Research: Martin Happ, Christian Maier, Jia Lei Du, Matthias Herlich, Salzburg Research Forschungsgesellschaft mbH
| 15:00-15:30
| Problem Statement – Using weather info for radio link failure (RLF) prediction (Turkcell, Turkey)
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PS-036.1 Radio Link Failure Prediction [Presentation] [GitHub Repo]
Link Busters: Dheeraj Kotagiri, Anan Sawabe , Takanora Iwai, NEC Corporation, Japan
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PS-036.2 Radio Link Failure (RLF) Prediction using Weather Information [Presentation] [GitHub Repo]
IEC_Research: Juan Samuel Pérez, Amín Deschamps, Willmer Quiñones, Yobany Díaz, INTEC University, Dominican Republic
| 15:30-15:45
| Problem Statement – Traffic recognition and Long-term traf-fic forecasting based on AI algorithms and metadata for 5G/IMT-2020 and beyond (SPbSUT)
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PS-038.1 Traffic recognition and long-term traffic forecasting based on AI algorithms and metadata [Presentation] [GitHub Repo]
USATU: Ainaz Hamidulin, Viktor Adadurov, Denis Garaev, Artem Andriesvky, USATU University, Russia
| 15:45-16:30
| Problem Statement – ML5G-PHY- Channel Estimation @NCSU: Machine Learning Applied to the Physical Layer of Millimeter-Wave MIMO Systems at North Carolina State University (NCSU, US)
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PS-025.1 Learning to detect: on site-specific channel estimation with hybrid MIMO architectures [Presentation] [GitHub Repo]
ML-DOJO: Dolores Garcia, Joan Palacios, Joerg Widmer, IMDEA Networks, Spain
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PS-025.2 Sparse Bayesian Learning for Site-Specific Hybrid MIMO Channel Estimation [Presentation] [GitHub Repo]
ICARUS: Emil Björnson, Pontus Giselsson, Mustafa Cenk Yetis, Özlem Tugfe Demir, Linköping University and Lund University, Sweden
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PS-025.3 A Multilevel-Greedy and Bayesian Compressive Channel Estimator for Frequency-Selective Hybrid mmWave MIMO Systems [Presentation] [GitHub Repo]
Learned Chester: Chandra Murthy, Christo Kurisummoottil Thomas, Marios Kountouris, Rakesh Mundlamuri, Sai Subramanyam Thoota, Sameera Bharadwaja H, Eurecom, France, and Indian Institute of Science, India
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Day 3 -Thursday, 17 December 2020 (Time zone - CET)Watch Video Recording (17 December event)
11:30-12:00
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Join session to test connection | 12:00-12:30
| Opening Ceremony
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Welcome remarks:
Houlin Zhao, Secretary General, ITU
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Welcome remarks: TSB Dir Chaesub Lee, Director, Telecommunication Standardization Bureau, ITU
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Welcome remarks: H.E. Eng. Majed Sultan Al Mesmar, Deputy Director General Telecommunication Regulatory Authority
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ITU AI/ML in 5G Challenge - The Journey Slides: Thomas Basikolo, ITU
| | 12:30-12:55 |
Keynote – Recent advances in Federated Learning for Communication
Speaker: Wojciech Samek, Fraunhofer HHI
| | 12:55-13:40 |
Special Session: Vision for the future - AI/ML in 5G roadmap
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Regulator Perspective: TRA-UAE
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Industry Perspective: Bob Everson, Senior Director, 5G Architecture Cisco
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Industry Perspective: Wei Meng, Director of Standard and Open Source Planning, ZTE Corporation
| 13:40-14:05
| Keynote: The Unfinished Journey of Network AI
Speaker: Dr. Chih-Lin I (Chief Scientist, Wireless Technologies, China Mobile Research Institute) | 14:05-14:30
| Keynote: Learning at the Wireless Edge
Speaker: H. Vincent Poor - Professor of Electrical Engineering - Princeton University
| 14:30-15:15
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Final Presentation: Overview of the solutions from the Challenge from 3 representative Teams | 15:15-15:30
| Award announcements: prizes and certificates
| 15:30- 15:35
| Call for papers: Special issue of ITU Journal on Future and Evolving Technologies (ITU J-FET)): “AI/ML Solutions in 5G and Future Networks”
Speaker: Alessia Magliarditi, ITU <Slides> | 15:35-15:45
| 2021 outlook for Challenge 2.0 Slides
Speaker: Vishnu Ram
| 15:45-16:00
| Closing Ceremony
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Closing remarks: Remarks from some hosts of the 2020 Challenge
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TSB Dir Chaesub Lee, Director, Telecommunication Standardization Bureau, ITU
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