Description

This is the second workshop of the 10 th Moratuwa Engineering Research Conference 2024 (MERCon 2024) which was organized by the Engineering Research Unit, University of Moratuwa. Abstract Artificial intelligence (AI) and machine learning (ML) stand out as some of the most pivotal technologies today. Notably, deep learning has spearheaded numerous breakthroughs across diverse domains, including computer vision, natural language processing, and speech recognition. Therefore, it is a natural question to ask: what role will AI/ML play in the domain of wireless communications? This workshop tries to shed some light on this question by introducing fundamental concepts of deep learning and illustrating their applications to wireless communications. Objectives • Understand the fundamentals of machine learning and its applications in communication systems. • Identify different machine learning approaches relevant to the physical layer. • Design and implement machine learning models to solve physical layer problems. • Understand the concept of end-to-end learning and the challenges associated with it Goals The workshop aims to introduce participants to the fundamentals of machine learning and then apply the machine learning principles for the design and optimisation of wireless communications systems and mobile networks. Relevance to Engineering Discipline Machine learning is anticipated to have a growing impact on the future advancements of 5G and the emergence of 6G. Therefore, this workshop provides an excellent chance to delve into the latest research in communications and deep learning, with a specific emphasis on hands-on implementation using cutting-edge deep learning libraries. Expected Outcomes • Skill Enhancement: Participants acquire new skills, knowledge, and practical insights related to applying machine learning in wireless communication systems. • Networking Opportunities: Workshops facilitate networking among participants, speakers, and organizers. • Dissemination of Knowledge: This Workshop facilitates the dissemination of knowledge, best practices, and our research findings. Target Audience: – This workshop mainly targets students, researchers, and practitioners who are new to their respective fields of study. Workshop Outline Duration: 3 hours Format: In-person with interactive hands-on exercises. The attendees will receive detailed Jupyter notebooks with code examples. Activities and Schedule: 1. Introduction to ML basics [1 hour] • What is ML/AI? • Advanced Neural Network Architectures 2. Applications of deep learning for communications [2 hours] • Deep learning for detection • Deep learning for channel estimation • End-to-end learning