Recent Submissions

  • AI-powered edge computing evolution for beyond 5G communication networks 

    Kartsakli, Elli; Pérez Romero, Jordi; Sallent Roig, Oriol; Bartzoudis, Nikolaos; Frascolla, Valerio; Mohalik, Swarup Kumar; Metsch, Thijs; Antonopoulos, Angelos; Tuna, Ömer Faruk; Deng, Yansha; Tao, Xin; Serrano, Maria A.; Quiñones Moreno, Eduardo (Institute of Electrical and Electronics Engineers (IEEE), 2023)
    Conference report
    Open Access
    Edge computing is a key enabling technology that is expected to play a crucial role in beyond 5G (B5G) and 6G communication networks. By bringing computation closer to where the data is generated, and leveraging Artificial ...
  • A tutorial on the characterisation and modelling of low layer functional splits for flexible radio access networks in 5G and beyond 

    Pérez Romero, Jordi; Sallent Roig, Oriol; Gelonch Bosch, Antonio José; Gelabert Doran, Xavier; Klaiqi, Bleron; Kahn, Marcus; Campoy García, David (Institute of Electrical and Electronics Engineers (IEEE), 2023-10)
    Article
    Open Access
    The centralization of baseband (BB) functions in a radio access network (RAN) towards data processing centres is receiving increasing interest as it enables the exploitation of resource pooling and statistical multiplexing ...
  • A deep q network-based multi-connectivity algorithm for heterogeneous 4G/5G cellular systems 

    Hernández Carlón, Juan Jesús; Pérez Romero, Jordi; Sallent Roig, Oriol; Vilà Muñoz, Irene; Casadevall Palacio, Fernando José (Springer, 2022)
    Conference report
    Restricted access - publisher's policy
    Multi-connectivity, which allows a user equipment to be simultaneously connected to multiple cells from different radio access network nodes that can be from a single or multiple radio access technologies, has emerged as ...
  • Deep learning-based multi-connectivity optimization in cellular networks 

    Hernández Carlón, Juan Jesús; Pérez Romero, Jordi; Sallent Roig, Oriol; Vilà Muñoz, Irene; Casadevall Palacio, Fernando José (2022)
    Conference lecture
    Restricted access - publisher's policy
    Multi-connectivity emerges as a useful feature to handle the traffic in heterogeneous cellular scenarios and fulfill the demanding requirements in terms of data rate and reliability. It allows a device to be simultaneously ...
  • On the implementation of a reinforcement learning-based capacity sharing algorithm in O-RAN 

    Vilà Muñoz, Irene; Sallent Roig, Oriol; Pérez Romero, Jordi (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference lecture
    Restricted access - publisher's policy
    The capacity sharing problem in Radio Access Network (RAN) slicing deals with the distribution of the capacity available in each RAN node among various RAN slices to satisfy their traffic demands and efficiently use the ...
  • Marco de desarrollo software e implementación de algoritmos de inteligencia artificial para la gestión de redes radio 5G 

    Vilà Muñoz, Irene; Sallent Roig, Oriol; Pérez Romero, Jordi (2022)
    Conference report
    Open Access
    The increase in complexity of 5G and beyond mobile communications networks to accommodate multiple services with stringent requirements has led to the introduction of Artificial Intelligence (AI) capabilities for automating ...
  • RAN slicing for multi-tenancy support in a WLAN scenario 

    Koutlia, Katerina; Umbert Juliana, Anna; García Escriche, Sergio; Casadevall Palacio, Fernando José (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    Conference lecture
    Restricted access - publisher's policy
    Radio Access Network (RAN) slicing is a key technology, based on Software Defined Networks (SDN) and Network Function Virtualization (NFV), which aims at providing a more efficient utilization of the available network ...
  • On the value of context awareness for relay activation in beyond 5G radio access networks 

    Pérez Romero, Jordi; Sallent Roig, Oriol (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    This paper envisions to augment the Radio Access Network (RAN) infrastructure in Beyond 5G(B5G) systems by exploiting relaying capabilities of user equipment (UE) as a way to improve the coverage, capacity and robustness. ...
  • On relay user equipment activation in beyond 5G radio access networks 

    Pérez Romero, Jordi; Sallent Roig, Oriol; Ruiz García, Olga (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    This paper envisages a Beyond 5G (B5G) Radio Access Network (RAN) in which the relaying capabilities offered by user equipment (UE) are used as a way to improve the coverage and robustness of the network. The paper proposes ...
  • On alleviating cell overload in vehicular scenarios 

    Trullenque Ortiz, Martín; Sallent Roig, Oriol; Camps Mur, Daniel; Escrig, Josep; Herranz Claveras, Carlos; Nasreddine, Jad; Pérez Romero, Jordi (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Open Access
    Fifth Generation (5G) networks will support countless new applications and new business models. One of the 5G paradigms is network slicing, which enables the integration of multiple logical networks each one tailored to ...
  • On the training of reinforcement learning-based algorithms in 5G and beyond radio access networks 

    Vilà Muñoz, Irene; Pérez Romero, Jordi; Sallent Roig, Oriol (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Conference report
    Restricted access - publisher's policy
    Reinforcement Learning (RL)-based algorithmic solutions have been profusely proposed in recent years for addressing multiple problems in the Radio Access Network (RAN). However, how RL algorithms have to be trained for a ...
  • Impact analysis of training in deep reinforcement learning-based radio access network slicing 

    Vilà Muñoz, Irene; Pérez Romero, Jordi; Sallent Roig, Oriol; Umbert Juliana, Anna (2022)
    Conference report
    Restricted access - publisher's policy
    Deep Reinforcement Learning (DRL) has recently emerged as a promising technique to deal with different problems in the 5G and beyond Radio Access Network (RAN). The practical implementation of DRL solutions in the real ...

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