The Role of Artificial Intelligence in Next-Generation Wireless Networks - an Overview of Technological and Law Implications

This thesis explores how artificial intelligence (AI) will benefit next-generation wireless networks focusing both on the technological aspects and legal implications. At first, a summary of AI history is provided, together with an overview of the different AI methodologies. Among them, the thesis focuses on machine learning-based approaches and in particular neural network algorithms for wireless networks. The second chapter examines how AI can support wireless network management and explores the advantages of adopting this new paradigm as a substitute for current non-data-driven approaches. Next, we discuss the technical challenges that should be addressed for the practical integration of AI within wireless networks, starting from the huge amount of data needed to properly configure AI methodologies and the high computational demand. Emerging approaches that will allow overcoming the above-mentioned challenges, such as, e.g., the placement of computational servers near the base stations and the adoption of federated learning techniques, are also discussed. In the third chapter, we examine the cybersecurity risks that arise with the adoption of AI in wireless networks, and the necessary regulations that will help address these risks. A vision of the future of AI in wireless networks, and a discussion of the open research challenges from technological and legal points of view conclude the thesis.