Wireless and Satellite Communications

AI and Machine Learning for Wireless and Satellite Networks

Artificial intelligence and machine learning are increasingly transforming the design and operation of wireless and satellite networks. This track explores how data-driven approaches enable intelligent decision-making across various network layers. Participants will examine applications of machine learning in channel estimation, interference management, resource allocation, and mobility prediction, enhancing network efficiency and adaptability.

The track also addresses challenges related to data availability, model complexity, and real-time implementation in communication systems. Techniques such as federated learning, reinforcement learning, and distributed intelligence are discussed in the context of wireless and satellite networks. By integrating AI and ML into network management and optimization, this track highlights the pathway toward self-learning, autonomous communication systems