Abstract
<jats:p>The rapid evolution of wireless communication technologies, particularly with the advent of 5G and the anticipated 6G networks, has brought forth new challenges in network management, security, and performance optimization. Artificial Intelligence (AI) and Machine Learning (ML) frameworks are emerging as transformative solutions for addressing these complexities, enabling autonomous network operations, intelligent resource management, and enhanced security protocols. This book chapter explores the integration of AI and ML techniques across various aspects of advanced wireless networks, with a specific focus on real-time network optimization, privacy protection, interference management, and network slicing. The role of AI in optimizing Quality of Service (QoS) through hybrid models, as well as leveraging unsupervised learning for interference identification and management, is critically examined. Moreover, the chapter highlights the growing importance of AI-driven network slicing and virtualization, particularly in the context of multi-tier networks for 6G environments. Machine learning-based solutions for real-time monitoring, adaptive network management, and privacy preservation in IoT networks are also discussed, emphasizing their potential to transform the security landscape of future wireless communication systems. This chapter offers valuable insights into the future directions of AI and ML applications, providing a comprehensive understanding of how these technologies will shape the next generation of wireless networks, making them more scalable, secure, and efficient.</jats:p>