Recent Submissions

  • 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)
    Conference report
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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)
    Conference report
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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)
    Conference report
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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)
    Conference report
    Restricted access - publisher's policy
    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)
    Conference lecture
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    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)
    Conference report
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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)
    Conference lecture
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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)
    Conference report
    Restricted access - publisher's policy
    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)
    Conference report
    Open Access
    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 ...
  • Dynamic resource allocation in C-RAN with real-time traffic and realistic scenarios 

    Guerra Gómez, Rolando; Ruiz Boqué, Sílvia; García Lozano, Mario; Olmos Bonafé, Juan José (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    Conference report
    Restricted access - publisher's policy
    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 ...
  • A machine learning enabled network planning tool 

    Moysen Cortes, Jessica; Giupponi, Lorenza; Mangues Bafalluy, Josep (Institute of Electrical and Electronics Engineers (IEEE), 2016)
    Conference report
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    In the coming years, planning future mobile networks will be infinitely more complex than nowadays. Future networks are expected to present multiple Network Management (NM) challenges to operators, such as managing network ...
  • Self coordination among SON functions in LTE heterogeneous networks 

    Moysen Cortes, Jessica; Giupponi, Lorenza (Institute of Electrical and Electronics Engineers (IEEE), 2015)
    Conference report
    Restricted access - publisher's policy
    In a self-organized Long Term Evolution (LTE) network, different Self-Organizing Network (SON) functions or different instances of the same SON function can execute parallel actions, which interact or collide among each ...

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