The design of Open Radio Access Network (O-RAN) compliant systems for configuring the virtualized Base Stations (vBSs) is of paramount importance for network operators. This task is challenging since optimizing the vBS scheduling procedure requires knowledge of parameters, which are erratic and demanding to obtain in advance. In this paper, we propose an online learning algorithm for balancing the performance and energy consumption of a vBS. This algorithm provides performance guarantees under unforeseeable conditions, such as non-stationary traffic and network state, and is oblivious to the vBS operation profile. We study the problem in its most general form and we prove that the proposed technique achieves sub-linear regret (i.e., zero average optimality gap) even in a fast-changing environment. By using real-world data and various trace-driven evaluations, our findings indicate savings of up to 74.3% in the power consumption of a vBS in comparison with state-of-the-art benchmarks.
|Title of host publication||Proceedings of the GLOBECOM 2022 - 2022 IEEE Global Communications Conference|
|Place of Publication||Piscataway|
|Number of pages||7|
|Publication status||Published - 2022|
|Event||GLOBECOM 2022 - 2022 IEEE Global Communications Conference - Rio de Janeiro, Brazil|
Duration: 4 Dec 2022 → 8 Dec 2022
|Name||2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings|
|Conference||GLOBECOM 2022 - 2022 IEEE Global Communications Conference|
|City||Rio de Janeiro|
|Period||4/12/22 → 8/12/22|
Bibliographical noteGreen Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
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