Enabling Intelligent Traffic Steering in A Hierarchical Open Radio Access Network

Nguyen, Van-Dinh; Vu, Thang X.; Nguyen, Nhan Thanh; Nguyen, Dinh C.; Juntti, Markku; Luong, Nguyen Cong; Hoang, Dinh Thai; Nguyen, Diep N.; Chatzinotas, Symeon (2024-02-26)
 
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https://doi.org/10.1109/GLOBECOM54140.2023.10437249

Nguyen, Van-Dinh
Vu, Thang X.
Nguyen, Nhan Thanh
Nguyen, Dinh C.
Juntti, Markku
Luong, Nguyen Cong
Hoang, Dinh Thai
Nguyen, Diep N.
Chatzinotas, Symeon
IEEE
26.02.2024

V. -D. Nguyen et al., "Enabling Intelligent Traffic Steering in A Hierarchical Open Radio Access Network," GLOBECOM 2023 - 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia, 2023, pp. 5232-5237, doi: 10.1109/GLOBECOM54140.2023.10437249.

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doi:https://doi.org/10.1109/globecom54140.2023.10437249
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https://urn.fi/URN:NBN:fi:oulu-202403202353
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Abstract

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 0- RAN that are completely automated, offering improved control and flexibility.
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