We call for original and unpublished papers, which must be formatted in the standard IEEE two-column format that is used by the INFOCOM 2026 main conference, and must not exceed six pages in length (including references). All submitted papers will go through a strict peer review process, and all accepted papers that are presented by one of the authors at the workshop will be published in the IEEE INFOCOM 2026 workshop proceedings and IEEE Xplore.
Please submit your papers in PDF format via edas https://edas.info/N34577.
Submission Deadline: December 29, 2025 January 16, 2026
Notification of Acceptance: February 5, 2026
Camera Ready: March 2, 2026
Workshop: May 18, 2026
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 wireless traffic analysis
Generative Models (e.g., LLM, Diffusion Models) for Wireless Data Synthesis
Large Language Models and Multi-modal Large Models for Wireless Communications, Sensing, and Security
Federated Learning for Wireless Communications, Sensing, and Security
AI-driven Digital Twins for Wireless Communications, Sensing, and Security
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
Professor Jie Xu, The Chinese University of Hong Kong, Shenzhen, China. xujie@cuhk.edu.cn
Dr. Junqing Zhang, University of Liverpool, UK, junqing.zhang@liverpool.ac.uk
Dr. Xuyu Wang, Florida International University, USA, xuywang@fiu.edu
Dr. Francesca Meneghello, , Northeastern University, USA. fr.meneghello@northeastern.edu
Tommaso Melodia (Northeastern University, USA)
Title: Open 6G: Orchestration, Automation, Conflict Management, and Explainability in AI-Powered nextG Wireless Systems
Federico Chiariotti (University of Padova, Italy):
Title: From semantic communication to goal-oriented networking
08:30–08:40
Opening Session
08:40–10:00
Session 1: Wireless Communications
Lightweight Deep Learning-Aided LDPC Decoding for 5G NR UAV Communications
Carla Estefania Garcia (University of Luxembourg, Luxembourg); Mario Rodrigo Camana (University of Luxembourg, Luxembourg); Jorge Querol (University of Luxembourg, Luxembourg); Symeon Chatzinotas (University of Luxembourg, Luxembourg)
Site-Specific Learning in Pinching Antenna System
Jia Guo (Queen Mary University of London, United Kingdom (Great Britain)); Chongjun Ouyang (Queen Mary University of London, United Kingdom (Great Britain) & University College Dublin, Ireland); Deqiao Gan (Huazhong University of Science and Technology, China); Hao Jiang (Queen Mary University of London, United Kingdom (Great Britain)); Yuanwei Liu (The University of Hong Kong, Hong Kong); A Nallanathan (QMUL, United Kingdom (Great Britain))
Sequence-Model-Based Joint CSI Feedback and Dynamic Multiuser Precoding for FDD Massive MIMO Systems
Weiqiang Tan (Guangzhou University, China); Minwei Zhang (Guangzhou University, China); Jintao Wang (Jinan University, China); Binggui Zhou (Imperial College London, United Kingdom (Great Britain)); Xiyuan Chen (Southeast University, China); Chunguo Li (Southeast University, China)
PASS-Aided Over-the-Air Computation via A Graph-based Proximal Policy Optimization Approach
Meng Zhang (Queen Mary University of London, United Kingdom (Great Britain)); Ruikang Zhong (Queen Mary University of London, United Kingdom (Great Britain)); Yixuan Zou (Queen Mary University of London, United Kingdom (Great Britain)); Hyundong Shin (Kyung Hee University, Korea (South)); Yuanwei Liu (The University of Hong Kong, Hong Kong)
Computation Offloading and Resource Allocation for RIS-Aided Low-Altitude Wireless Networks
Qihong Liu (Communication University of China, China); Fangfang Yin (Communication University of China, China); Wanli Ni (Beijing University of Posts and Telecommunications, China); Ye Hu (University of Miami, USA); Yu Zhang (Tsinghua University, China); Libiao Jin (Communication University of China, China); Shufeng Li (Communication University of China, China)
10:00–10:30
Coffee Break
10:30–11:30
Keynote Session I
Federico Chiariotti (University of Padova, Italy)
Title: From semantic communication to goal-oriented networking
11:30–12:34
Session 2: Wireless Security
Explainable Efficiency: Grad-CAM Analysis of Image-Based Radio Frequency Fingerprinting
Ingrid Huso (Hamad Bin Khalifa University, Qatar); Savio Sciancalepore (Eindhoven University of Technology (TU/E), The Netherlands); Gabriele Oligeri (Hamad Bin Khalifa University, Qatar); Giuseppe Piro (Politecnico di Bari, Italy); Gennaro Boggia (Politecnico di Bari, Italy)
Cross-Domain RF Fingerprinting with FDA-based Representations and Few-Shot Learning
Yujie Sun (Auburn University, USA); Rohan Kumar (Florida International University, USA); Tianya Zhao (Florida International University, USA); Yiting Wang (Florida International University, USA); Bolin Xiang (Bridgeland High School, USA); Shiwen Mao (Auburn University, USA); Xuyu Wang (Florida International University, USA)
A New UAV Identification Method Based on Multi-Domain Prior Information Extraction and Cross-Environment Composite Loss Regularization
Yunhong He (Nanjing University of Aeronautics and Astronautics, China); Zhipeng Lin (NanJing University of Aeronautics and Astronautics, China); Yongjie Xu (Nanjing University of Aeronautics and Astronautics, China); Jie Zeng (Beijing Institute of Technology, China); Qiuming Zhu (Nanjing University of Aeronautics and Astronautics & XYZ Company, China); Qihui Wu (Nanjing University of Aeronautics and Astronautics, China)
Federated Learning Improves Metasource-Based Secret Key Generation with Low-Density Parity-Check Coding
Quan Zhang (Soochow University, China); Yuli Yang (Soochow University, China); Jide Yuan (Soochow University, China); Mohsen Guizani (Mohamed Bin Zayed University of Artificial Intelligence, United Arab Emirates)
12:30 – 14:00
Lunch Break
14:00–15:00
Keynote Session II
Tommaso Melodia (Northeastern University, USA)
Title: Open 6G: Orchestration, Automation, Conflict Management, and Explainability in AI-Powered nextG Wireless Systems
15:00–15:32
Session 3: Spectrum Mapping
Adaptive Spectrum Mapping: An Attention-Based Deep Reinforcement Learning Approach with Sparse Gaussian Processes
Yiran Chen (Nanjing University of Aeronautics and Astronautics, China); Qiuming Zhu (Nanjing University of Aeronautics and Astronautics & XYZ Company, China); Jie Wang (Nanjing University of Aeronautics and Astronautics, China); Ziye Jia (Nanjing University of Aeronautics and Astronautics, China); Zhipeng Lin (NanJing University of Aeronautics and Astronautics, China); Guochen Gu (Nanjing University of Aeronautics and Astronautics, China); Xuan Wang (Nanjing University of Aeronautics and Astronautics, China); Qihui Wu (Nanjing University of Aeronautics and Astronautics, China)
Multi-aspect Robust Adaptive Streaming Tensor Completion for Space-based Spectrum Situation Map Construction
Xianping Qin (Shenzhen University & College of Electronic and Information Engineering, China); Yuan Ma (Shenzhen University, China); Xingjian Zhang (Harbin Institute of Technology (Shenzhen), China); Ruifeng Xiao (Fudan University, China); Xiaowen Cao (Shenzhen University, China); Jian Jiao (Harbin Institute of Technology - Shenzhen, China)
15:30–16:00
Coffee Break
16:00–17:04
Session 4: Network Traffic Prediction
Autonomous Spatiotemporal Graph Learning for Proactive Edge-Based Traffic Forecasting
Pan Ruifeng (City University of Macau, Macao & Nanchang Vocational University, China); Chun Wang (City University of Macau, Macao); Nan Zhao (Hubei University of Technology, China); Zhigang Ma (Nanchang University, China)
PP-OpenNet: Privacy-Preserved Open Set Classification for Network Traffic
Jingze Zhang (The Chinese University of Hong Kong, Hong Kong); Leijie WU (Huawei Technologies, China); Xi Peng (Huawei Technologies Co., Ltd., Hong Kong); Qingqing Yang (Huawei Theory Lab, Hong Kong); Ruilun Liu (University of Hong Kong, Hong Kong); Hong Xu (The Chinese University of Hong Kong, Hong Kong)
Multi-Scale Transformer Diffusion Model for Realistic Wireless Network Traffic Synthesis
Zhongxu Si (Beijing University of Posts and Telecommunications, China); Yong Zhang (Beijing University of Posts and Telecommunications, China); Lei Yao (Beijing University of Posts and Telecommunications, China); Guo Da (Beijing University of Posts and Telecommunications, China); Yinglei Teng (Beijing University of Posts and Telecommunications, China); Xiaolei Hua (China Mobile Research Institute, China); Renkai Yu (China Mobile Research Institute, China); Lin Zhu (China Mobile Research Institute, China)
Decoupled Generalizable Spatiotemporal Learning for Wireless Traffic Prediction
Qi Li (Beijing University of Posts and Telecommunications, China); Lei Yao (Beijing University of Posts and Telecommunications, China); Zhenyu Zhang (Beijing University of Posts and Telecommunications, China); Shihang Wang (Beijing University of Posts and Telecommunications, China); Yong Zhang (Beijing University of Posts and Telecommunications, China); Lin Zhu (China Mobile Jiutian Research, China); Xiaolei Hua (China Mobile Jiutian Research, China); Renkai Yu (China Mobile Research Institute, China)
17:07–17:55
Session 5: Emerging Techniques and Applications
Spiking Personalized Federated Learning for Brain-Computer Interface-Enabled Immersive Communication
Chen Shang (University of Technology Sydney, Australia); Hoang Thai Dinh (University of Technology Sydney (UTS), Australia); Diep N. Nguyen (University of Technology Sydney, Australia); Jiadong Yu (The Hong Kong University of Science and Technology (Guangzhou), China)
LRAF: LLM-Assisted Risk-Attribute Framework for Phishing Email Detection
Yulin Zhang (Xidian University, China); Ruidong Li (Kanazawa University, Japan); Xinghua Li (XIDIAN University, China); Zhang Yu qing (Graduate University of Chinese Academy of Science, China)
Semantic-Aware Attention-Driven JSCC for Efficient Video Transmission over Wireless Channels
Gianvito Coppola (Politecnico di Bari, Italy); Mahshid Narimani Kenari (Politecnico di Bari, Italy); Giancarlo Sciddurlo (Politecnico di Bari & CNIT, Italy); Nicola Cordeschi (Polytechnic University of Bari, Italy); Luigi Alfredo Grieco (Politecnico di Bari, Italy); Gennaro Boggia (Politecnico di Bari, Italy)
17:55 – 18:00
Closing Session