Adaptive network management in 6G O-RAN: a framework for dynamic user demands

Abstract

The advent of Sixth Generation (6G) mobile networks heralds a transformative era in wireless communication, demanding unprecedented adaptability and energy efficiency to meet burgeoning dynamic user demands. This thesis introduces an innovative framework for adaptive network management within the Open Radio Access Network (O-RAN) paradigm, focusing on the integration of its dynamic architecture. The framework emphasizes the exploration of integration components to manage and optimize the Radio Access Network (RAN). Central to this framework are the architectural components of O-RAN: the Service Management and Orchestration (SMO), the Near-Real-Time RAN Intelligent Controller (Near-RT RIC), and the Non-Real-Time RAN Intelligent Controller (Non-RT RIC), each playing a crucial role in enhancing network adaptability and operational efficiency. The proposed framework leverages the open and intelligent architecture of O-RAN, deploying various applications such as the rApp Energy Savings to optimize energy consumption and data flow management. It aims to establish a new benchmark for network management in the 6G era by integrating real-time data analytics, intelligent policy implementation, and adaptive energy management strategies. While energy savings is a primary use case for validating our dynamic architecture, it is important to note that the framework’s flexibility allows for the integration of other applications as well. The dynamic clustering mechanism for radio nodes, coupled with the RIC, facilitates efficient resource management by adjusting network configurations based on current and predicted traffic loads, significantly improving resource utilization and energy efficiency. A prototype implementation validates the framework under various network conditions and user demands, demonstrating substantial improvements in resource utilization and energy efficiency compared to traditional static network management approaches. The adaptive framework significantly reduces energy consumption during low-demand periods while maintaining high performance during peak times. The effectiveness of the proposed framework is demonstrated through its dynamic management of network resources, facilitated by specialized rApps and xApps. These applications interface with the SMO, Near-RT RIC, and Non-RT RIC, contributing to substantial improvements in network performance. Key components such as the modified VespaMgr and A1 Mediator within the Near-RT RIC, along with custom SMO elements, ensure seamless communication and integration across the network. This dynamic architecture has shown significant enhancements in resource utilization and energy efficiency. The results indicate efficient data handling and communication through the O1 interface for VES, validating the framework’s capability to adapt to varying network conditions and demands, thereby establishing new benchmarks in 6G network management.