Intent-Driven Closed-Loop Control and Management Framework for 6G Open RAN

Abstract

Future mobile networks should provide on-demand services for various industries and applications with the stringent guarantees of quality of experience (QoE), which highly challenge the flexibility of network management. However, the diverse requirements of QoE and the management of heterogeneous networks create significant pressure towards communication service providers (CSPs). In the 6th generation mobile networks, the CSPs should guarantee resilient performance for the communication service consumers with less human involvement. In this work, we turn to intent-driven network and on-demand slice management, and to decrease the complexity and cost in full life cycle slice management, we first present an intentdriven closed-loop (CL) control and management framework that automates the deployment of network slices and manages resources intelligently based on the extended CL architecture. And then, we explore and exploit the deep reinforcement learning algorithm to address the problem of resource allocation, which is formulated as a Markov decision process. Finally, we demonstrate the feasibility of the proposed framework by deploying the open radio access network (RAN) infrastructure in OpenAirInterface platform and realizing the CL control and management with near real-time RAN intelligent controller. The emulation results demonstrate the effectiveness of slicing performance, measured in terms of delay and rate.

IDR: Intent‐driven routing strategy for reliable and cost‐effective multicasting in airborne tactical networks

“…However, in legacy network paradigms, the deployment of BIER depends on manual configuration, resulting in low efficiency of net- work operation and maintenance. The advent of intent-driven networking (IDN) has made automated, hands-off network management a reality [15][16][17]. Besides, IDN can also understand high-level routing intents and provides high routing efficiency [18,19].…”