Empowering Next-Gen Networks: AI-Driven Autonomy in O-RAN and SON Architectures

Wireless communication plays a crucial role in evolving next-generation networks. Open Radio Access Networks (O-RAN), Self-Organizing Networks (SON), and Artificial Intelligence (AI)-driven automation are set to revolutionize network operations by enhancing flexibility, scalability, intelligence, and efficiency. Integrating AI and Machine Learning (ML) into O-RAN and SON enables autonomous network management, dynamically optimizing performance, resource allocation, and fault recovery. SON enhances network self-configuration, self-optimization, and self-healing capabilities, reducing operational costs and improving service reliability. This paper examines the potential of AI-driven autonomy in O-RAN and SON, with a focus on their combined impact on next-generation wireless networks. With its open and intelligent architecture, O-RAN can provide flexibility and adaptability for SON functionalities. O-RAN’s open interfaces and modular components can help achieve greater control and customization of network resources. Both O-RAN and SON can significantly enhance network efficiency, scalability, and reliability, shaping the future of wireless networks. Network efficiency can be achieved through dynamic resource allocation, while improved scalability allows the network to accommodate the growing number of connected devices. Increased reliability is ensured through automated fault detection and recovery mechanisms. This study provides a comprehensive analysis of the synergies of AI-driven autonomy of O-RAN and SON, highlighting their technical and operational benefits. It also addresses potential challenges such as interoperability issues, security concerns, and the need for standardized protocols. The paper concludes with a discussion of the future directions and research opportunities in this domain, emphasizing the critical role of O-RAN and SON in shaping the evolution of autonomous next-generation wireless networks.