Coordination of smart B5G radio access and autonomous optical transport networks
(English) Future radio access network (RAN) will operate with massive and heterogeneous small-cell deployments and end-to-end (e2e) connectivity in support of diverse beyond fifth-generation (B5G) use cases. More and more connectivity services are requiring not only stringent but also more predictab...
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| Tipo de recurso: | tesis doctoral |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/425860 |
| Acceso en línea: | https://hdl.handle.net/2117/425860 https://dx.doi.org/10.5821/dissertation-2117-425860 |
| Access Level: | acceso abierto |
| Palabra clave: | 621.3 Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
| Sumario: | (English) Future radio access network (RAN) will operate with massive and heterogeneous small-cell deployments and end-to-end (e2e) connectivity in support of diverse beyond fifth-generation (B5G) use cases. More and more connectivity services are requiring not only stringent but also more predictable Quality of Service (QoS) performance, measured in terms of key performance indicators (KPI) such as throughput and capacity. With the advent of Open RAN (O-RAN), the implementation of flexible function splits/placement for guaranteeing target latency requirements and improved reliability is enabled. This smart operation must also precisely match capacity requirements, which typically reduces energy consumption, by managing the number of active base stations (BS) that are required to support user traffic requirements. In addition to RAN, access and metro optical networks play a fundamental role to meet e2e requirements, in terms of both capacity and latency. Thus, optical transport networks can operate autonomously, e.g., to adapt optical capacity to current traffic. Nevertheless, the foreseen B5G scenarios poses challenges to autonomous optical network operation, since smart RAN operation generates highly variable and unpredictable traffic. Indeed, smart operation of both RAN and fixed network makes difficult to achieve optimal e2e connectivity performance if they are done independently. Instead, both domains can share knowledge and coordinate with the objective of guaranteeing strict QoS requirements and efficient resource utilization of e2e connectivity services. This Ph.D. thesis is dedicated to developing solutions that coordinate both smart and autonomous operation of RAN and fixed optical network segments under B5G foreseen scenarios. To this aim, three goals are defined. The first goal aims at providing a methodology for smart operation of RAN cells with dense deployment of BSs, which is one of the most challenging scenarios envisioned for B5G networks. Relying on Open-RAN capabilities regarding monitoring and control loops, an AI-based approach that integrates both supervised and unsupervised machine learning algorithms to achieve intelligent RAN operation is proposed. The objective is to minimize energy consumption by switching on/off BSs while providing the desired coverage and required capacity needs. From the previous contributions and lessons learnt, the second goal focuses on analyzing the impact in terms of traffic to be supported by the underlying access and metro optical networks assuming smart RAN operation. The main conclusion of this goal is that smart RAN operation can have a critical affectation on underlying optical transport, which requires coordination between RAN and optical networks for efficient e2e network management. In light of the above, the third goal tackles two different use cases where coordination between smart RAN operation and autonomous optical network management provide benefits and allow e2e QoS assurance. On the one hand, a procedure for which RAN configuration changes to be performed are anticipated to the fixed network controller is proposed. By means of contextual data, fixed access and metro traffic prediction models are extended with RAN context in order to predict ongoing sharp traffic changes. On the other hand, a second use case focuses in the scenario of serving particular services where a maximum e2e delay need to be assured. In particular, a dynamic coordination mechanism is proposed, where actual RAN delay is informed in case that this exceeds a given level, so that the fixed network controller can adapt its budget and take decisions according to the new constraint. The research leading to these results has received funding from the Smart Networks and Services Joint Undertaking under the European Union's Horizon Europe research and innovation programme under Grant Agreement No. 101096120 (SEASON), and the MICINN IBON (PID2020-114135RB-I00) projects and from the ICREA Institution. |
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