Výsledky vyhledávání - "Joan Olmos Bonafe"

Akademický článek

Machine Learning Adaptive Computational Capacity Prediction for Dynamic Resource Management in C-RAN

Autor: Rolando Guerra-Gomez, Silvia Ruiz-Boque, Mario Garcia-Lozano, Joan Olmos Bonafe

Publikováno v: IEEE Access, Vol 8, Pp 89130-89142 (2020)

Efficient computational resource management in 5G Cloud Radio Access Network (C-RAN) environments is a challenging problem because it has to account simultaneously for throughput, latency, power efficiency, and optimization tradeoffs. The assumption

Externí odkaz: https://doaj.org/article/34b72febe8f0480ab5cef29c0b85d30d

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Machine-learning based traffic forecasting for resource management in C-RAN

Autor: Sílvia Ruiz Boqué, Mario Garcia-Lozano, Rolando Guerra-Gomez, Joan Olmos Bonafe

Publikováno v: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
EuCNC

The assumption of a fixed computational capacityat the Baseband Unit (BBU) pools in a Cloud Radio Access Network (C-RAN) deployment results in underutilized resourcesor unsatisfied users depending on traffic requirements. In thispaper a new strategy

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::22b1b71c45dfe2ef843e075f19a7e38d
https://hdl.handle.net/2117/345553

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Dynamic resource allocation in C-RAN with real-time traffic and realistic scenarios

Autor: Joan Olmos Bonafe, Mario Garcia-Lozano, Sílvia Ruiz Boqué, Rolando Guerra-Gomez

Publikováno v: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
WiMob

This work proposes the use of a modified and improved version of the realistic Vienna Scenario that was defined in COST action IC1004, to test two different scale C-RAN deployments. First, a large-scale analysis with 628 Macro-cells (Mcells) and 221

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1778bbc83f886f633a46bc6a46fee7c
https://hdl.handle.net/2117/184372

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