Enabling Intelligent Traffic Steering in A Hierarchical Open Radio Access Network

In this paper, we aim to enable an intelligent traffic (TS) steering application in the open radio access network (O-RAN) by jointly optimizing the flow-split distribution, congestion control and scheduling (i.e. so-called JFCS). To do so, we develop a multi-layer optimization framework based on network utility maximization and stochastic optimization methods. The proposed algorithm provides fast convergence, long-term utility-optimality and significantly low latency compared to state-of-the-art RAN approaches. In particular, our main contributions are as follows: i) we propose the novel JFCS framework to efficiently and adaptively route traffic to indented users in appropriate radio units, and ii) we develop low-complexity algorithms to effectively solve the JFCS problem in different time scales, enabling a closed-loop control of the TS in the O-RAN context. The insights presented in this work will pave the way for O-RAN that are completely automated, offering improved control and flexibility.