IEEE International Conference on Communications
9–13 June 2024 // Denver, CO, USA
Scaling the Peaks of Global Communications

WS-17: AI/ML-Powered Autonomous Telco Networks

WS-17: AI/ML-Powered Autonomous Telco Networks

The fifth-generation cellular network, 5G, presents increased complexities when compared to its predecessors. Factors such as diverse network environments, the surge in cell density, varying service demands make the design and management of 5G networks very challenging. Recently, the telecommunications industry has realized the indispensable nature of artificial intelligence (AI) and machine learning (ML) in actualizing a thoroughly automated wireless network, ranging from autonomous service quality assurance at upper layers to robust and intelligent physical-layer wireless algorithms. AI/ML are vital for not just curtailing operational costs but also tackling challenges of future wireless communications, including for example high speed connections in complex environments with unknown channel conditions as well as ultra-reliable and low latency communications in both the evolutionary 5G (B5G) and the forthcoming 6G networks. This workshop aims to bring together cutting-edge research efforts that tackle these intrinsic challenges and explore the vast potentialities ahead. Contributions from AI specialists, telecom professionals, and cross-disciplinary experts are welcomed. The focal themes for this edition encompass, but are not limited to:

  • AI/ML based physical layer technologies for B5G and 6G
  • Beamforming in massive MIMO system based on AI/ML
  • AI/ML based non-orthogonal multiple access (NOMA) techniques
  • Channel modeling based on AI/ML
  • AI/ML in network design and planning
  • AI/ML for coverage and capacity optimization
  • AI/ML based network load balancing and traffic steering
  • Intelligent network slicing
  • AI/ML for network deployment automation
  • AI/ML for service quality assurance and improvement
  • AI/ML self-driving networks
  • AI/ML for network energy saving and efficiency improvement
  • Reinforce Learning for Autonomous Networks
  • Federated Learning in Networking


Workshop Web Page


Important Dates

  • Workshop Paper Submission Deadline: 4 February 2024
  • Paper Acceptance Notification: 14 March 2024
  • Camera Ready: 15 March 2024
  • Accepted Author Registration Deadline: 15 March 2024


Submission Link


Workshop Chairs

  • Kai Yang:Tongji University, China
  • Yan Xin:Samsung Research America Inc., USA
  • Qi Bi:China Telecom, China
  • Xingqin Lin:NVIDIA, USA
  • Narayan Prasad:QUALCOMM, USA

Diamond Patrons

Silver Patrons

Bronze Patrons