Paper Submission Deadline: January 8, 2023
Authors Notification: February 6, 2023
Final Manuscript Due: March 6, 2023
Workshop: May 20, 2023
Deep learning has transformed many areas including the wireless domain. It has significantly unlocked the performance of wireless physical layer design, wireless sensing and wireless security. This workshop aims to bring together practitioners and researchers from both academia and industry for discussion and technical presentations on fundamental and practically relevant questions related to many challenges arising from deep learning for wireless communications, sensing and security. It also aims to provide the industry with fresh insight into the development of deep learning applications in wireless communication and networks.
In line with such objectives, original contributions, for both technical and demo sessions, are solicited on topics of interest to include, but not limited to, the following:
Deep learning for signal detection
Deep learning for channel modeling, estimation and prediction
Deep learning for resource optimization
Deep learning-based signal classification (including technology classification and modulation recognition)
Deep learning-based wireless sensing (including WiFi, mmWave radar, LoRa, RFID, etc)
Deep learning for localization and positioning
Deep learning for wireless security
Deep learning-based radio frequency fingerprint identification
Deep learning for physical layer security
Deep learning for network traffic analysis
Explainable artificial intelligence for deep learning-based wireless communications, sensing, and security
Deep learning for emerging communication applications including intelligent reflection surface, unmanned aerial vehicles
Deep learning for new Internet of things applications
Adversarial attacks on deep learning-based wireless communication, sensing, and security
Professor Shiwen Mao, Auburn University, USA, smao@auburn.edu
Professor Yingying Chen, Rutgers University, USA, yingche@scarletmail.rutgers.edu
Professor Carlo Fischione, KTH Royal Institute of Technology, Sweden, carlofi@kth.se
Dr. Junqing Zhang, University of Liverpool, UK, junqing.zhang@liverpool.ac.uk
Dr. Xuyu Wang, Florida International University, USA, xuywang@fiu.edu
Professor Kaushik Chowdhury, Northeastern University, USA
Professor Walid Saad, Virginia Tech, USA
Morning Sessions:
8:00-8:10 EDT
8:10-9:10 EDT
Professor Kaushik Chowdhury, Northeastern University, USA
Title: RF Fingerprinting: Challenges and Experiences in Real-world Applications
09:10 -10:30 EDT
Federated Radio Frequency Fingerprinting with Model Transfer and Adaptation
A Noise-Robust Radio Frequency Fingerprint Identification Scheme for Internet of Things Devices
Keep It Simple: CNN Model Complexity Studies for Interference Classification Tasks
A GAF and CNN based Wi-Fi Network Intrusion Detection System
10:30-11:00 EDT
11:00-11:40 EDT
WiWm-EP: Wi-Fi CSI-based Wheat Moisture Detection Using Equivalent Permittivity
ADAPTER: A DRL-based Approach to Tune Routing in WSNs
Afternoon Sessions:
14:00-15:00 EDT
Professor Walid Saad, Virginia Tech, USA
Title: Understand Me If You Can: Reasoning Foundations of Semantic Communication Networks
15:00-17:00 EDT
RIS-Empowered MEC for URLLC Systems with Digital-Twin-Driven Architecture
Multi-Agent Deep Reinforcement Learning for the Access Point Activation Strategy in Cell-Free Massive MIMO Networks
Untrained Neural Network based Bayesian Detector for OTFS Modulation Systems
Recurrent Neural Network Based RACH Scheme Minimizing Collisions in 5G and Beyond Networks
Shallow Neural Networks for Channel Estimation in Multi-Antenna Systems