IEEE International Conference on Computer Communications
17–20 May 2023 // New York area // USA

Workshop on Deep Learning for Wireless Communications, Sensing, and Security (DeepWireless) - Call for Papers

Workshop on Deep Learning for Wireless Communications, Sensing, and Security (DeepWireless)

Call for Papers


Scope and Topics of Interest

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

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