Sunday, October 29
8:45 - 9:00
Opening remarks
9:00 - 10:30
MIMO and Wireless Systems
- Quantifying Network Level Improvement due to Beamforming on the Performance of Large-Scale Dense Urban IoT Networks
- Spatial User Clustering and Power Control for Downlink MIMO-NOMA Systems
- Online Dependency-aware Task offloading in Cloudlet-based Edge Computing Networks
10:30 - 11:00
Coffee break
11:00 - 12:30
Internet of Things
- New Machine Learning Hybrid Models to Lower Position Errors for Bluetooth-Based Indoor Localizations
- Application-aware Energy Attack Mitigation in the Battery-less Internet of Things
- Spatial Anti-Void Querying in Large IoT Networks
12:30 - 13:30
Lunch break
13:30 - 15:00
Federated Learning and Wireless Systems
- HFedSNN: Efficient Hierarchical Federated Learning using Spiking Neural Networks
- Median-Krum: A joint Distance-Statistical based Byzantine-robust algorithm in Federated Learning
- Energy-aware Localization Protocol for Vehicular Networks
15:00 - 15:30
Coffee break
15:30 - 17:30
Wireless communications
- Catching the LoRa ADR bandit with a new Sheriff: J-LoRaNeS
- Two Hops IRS Optimization in Urban Mobile Environment
- Distributed Collaborative Learning in Wireless Mobile Communication
Monday, October 30
09:30 - 10:30
Keynote Speech
- Research Directions in Network Architectures and Protocols for Intelligent Digital Infrastructures
- JJ Garcia-Luna-Aceves (University of Toronto, Canada)
10:30 - 11:00
Coffee break
11:00 - 12:00
Demo
- Demo Abstract: Experimental 6G Research Platform for Digital Twin-Enabled Beam Management
- Demo-Abstract: A DTN System for Tracking Miners using GAE-LSTM and Contact Graph Routing in an Underground Mine
12:30 - 13:30
Lunch break
13:30 - 14:30
Panel discussion
- Panelists
- JJ Garcia-Luna-Aceves (University of Toronto, Canada), Douglas Blough (Georgia Institute of Technology, USA), Ahmed Helmy (University of North Carolina, USA)
14:30 - 15:00
Coffee break
15:00 - 17:00
Edge Computing and Wireless Networks
- Pre-Overload Migration Scheme for NFV-based Fog Computing
- Gated Recurrent Units for Blockage Mitigation in mmWave Wireless
- Fast and Optimal Beam Alignment for Off-the-Shelf mmWave Devices
- User-centric AP Clustering with Deep Reinforcement Learning for Cell-Free Massive MIMO