Ponències/Comunicacions de congressos: Enviaments recents

Ara es mostren els items 1-12 de 176

    • Flexible radio access network optimization with cell coordination 

      Ruiz Boqué, Sílvia; García Lozano, Mario; Guerra Gómez, Rolando; Saeed, Umar (2022)
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      This paper focuses on Beyond fifth generation (B5G) non-linear data modeling and decision-making tools to optimize cost reduction versus coverage-QoS tradeoff. Especially, the distribution of active Remote Radio Heads ...

    • SCHEMA: Service Chain Elastic Management with distributed reinforcement learning 

      Dalgkitsis, Anestis; Garrido Platero, Luis Ángel; Mekikis, Prodromos-Vasileios; Ramantas, Kostas; Alonso Zárate, Luis Gonzaga; Verikoukis, Christos (Institute of Electrical and Electronics Engineers (IEEE), 2021)
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      As the demand for Network Function Virtualization accelerates, service providers are expected to advance the way they manage and orchestrate their network services to offer lower latency services to their future users. ...

    • A collaborative statistical actor-critic learning approach for 6G network slicing control 

      Rezazadeh, Farhad; Chergui, Hatim; Blanco Botana, Luis; Alonso Zárate, Luis Gonzaga; Verikoukis, Christos (Institute of Electrical and Electronics Engineers (IEEE), 2021)
      Comunicació de congrés
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      Artificial intelligence (AI)-driven zero-touch massive network slicing is envisioned to be a disruptive technology in beyond 5G (B5G)/6G, where tenancy would be extended to the final consumer in the form of advanced digital ...

    • Evaluación de la implantación del aprendizaje basado en proyectos en la EPSC (2001-2003) 

      Alcober Segura, Jesús Ángel; Ruiz Boqué, Sílvia; Valero García, Miguel (Escola Universitària Politècnica de Vilanova i la Geltrú, 2001)
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      Aprendizaje basado en problemas o proyectos (a partir de ahora PBL) es el aprendizaje que se produce como resultado del esfuerzo que realiza el alumno para resolver un problema o llevar a cabo un proyecto. ...

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

      Guerra Gómez, Rolando; Ruiz Boqué, Sílvia; García Lozano, Mario; Olmos Bonafé, Juan José (Institute of Electrical and Electronics Engineers (IEEE), 2020)
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      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 ...

    • Unsupervised learning for detection of mobility related anomalies in commercial LTE networks 

      Moysen Cortes, Jessica; Ahmed, Furqan; García Lozano, Mario; Niëmela, Jarno (Institute of Electrical and Electronics Engineers (IEEE), 2020)
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      We propose an unsupervised learning based anomaly detection framework for identifying cells experiencing performance degradation due to mobility problems, in LTE networks. Handover failure rate is used as a performance ...

    • Big data-driven automated anomaly detection and performance forecasting in mobile networks 

      Moysen Cortes, Jessica; Ahmed, Furqan; García Lozano, Mario; Niëmela, Jarno (Institute of Electrical and Electronics Engineers (IEEE), 2020)
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      The massive amount of data available in operational mobile networks offers an invaluable opportunity for operators to detect and analyze possible anomalies and predict network performance. In particular, application of ...

    • Continuous multi-objective zero-touch network slicing via twin delayed DDPG and OpenAI gym 

      Rezazadeh, Farhad; Chergui, Hatim; Alonso Zárate, Luis Gonzaga; Verikoukis, Christos (Institute of Electrical and Electronics Engineers (IEEE), 2020)
      Comunicació de congrés
      Accés restringit per política de l'editorial
      Artificial intelligence (AI)-driven zero-touch network slicing (NS) is a new paradigm enabling the automation of resource management and orchestration (MANO) in multi-tenant beyond 5G (B5G) networks. In this paper, we ...

    • Real-time dynamic network slicing for the 5G radio access network 

      Maule, Massimiliano; Mekikis, Prodromos Vasileios; Ramantas, Kostas; Vardakas, John; Verikoukis, Christos (Institute of Electrical and Electronics Engineers (IEEE), 2019)
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      The 5G networks are expected to satisfy diverse use cases and business models with significant advancements in terms of capacity, reliability, and latency. The allocation and provisioning of network resources pose a challenge ...

    • On the use of existing 4G small cell deployments for 5G V2N communication 

      Saeed, Umar; Hämäläinen, Jyri; Mutafungwa, Edward; Wichman, Risto; González González, David; García Lozano, Mario (Institute of Electrical and Electronics Engineers (IEEE), 2019)
      Comunicació de congrés
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      We study the feasibility of the dense 4G and 5G cellular networks at sub-6 GHz and millimeter wave carriers for vehicle-to-network applications. For this purpose, road-side network coverage, signal-to-interference-plus-noise ...

    • On the feasibility of remote driving application over dense 5G roadside networks 

      Saeed, Umar; Hämäläinen, Jyri; García Lozano, Mario; González González, David (Institute of Electrical and Electronics Engineers (IEEE), 2019)
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      Remote driving (RD) is a critical backup option for an autonomous vehicle when it faces an unexpected situation on the road. Fifth generation (5G) mobile communication is a key enabler of RD providing link between the ...

    • Route-based radio coverage analysis of cellular network deployments for V2N communication 

      Saeed, Umar; Hämäläinen, Jyri; Mutafungwa, Edward; Wichman, Risto; González González, David; García Lozano, Mario (Institute of Electrical and Electronics Engineers (IEEE), 2019)
      Text en actes de congrés
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      Cellular vehicle-to-network (V2N) communication will be the backbone of the connected vehicles of future. One of the key requirements of the connected vehicles is a near universal coverage on the streets. Traditional radio ...