Brief Summary

Reference


  1. Principal investigator(s): J. M. Lopez-Soler
    European Commission H2020, Grant number 871428, 11/2019-04/2022
    "Beyond 5G Multi-Tenant Private Networks Integrating Cellular, Wi-Fi, and LiFi, Powered by Artificial Intelligence and Intent Based Policy (5G-CLARITY)", J. M. Lopez-Soler, 2022
    close
    @researchproject{5gclarity, code={Grant number 871428}, title={Beyond 5G Multi-Tenant Private Networks Integrating Cellular, Wi-Fi, and LiFi, Powered by Artificial Intelligence and Intent Based Policy (5G-CLARITY)}, org={European Commission H2020}, type={European}, author={J. M. Lopez-Soler}, year=2022, month=4, date1={11/2019}, date2={04/2022}, funding={393.125 €}, url1={https://www.5gclarity.com/}, twitter={https://twitter.com/5g_clarity?lang=en}, linkedin={https://www.linkedin.com/in/5g-clarity-project-1538111a4}, url0="http://wimunet.ugr.es/projects/5gclarity.php", logo="http://wimunet.ugr.es/assets/img/research/projects/h2020_logo.jpg", note="ongoing"}
    close


    This European project (European Commission H2020, Grant number 871428) is titled "Beyond 5G Multi-Tenant Private Networks Integrating Cellular, Wi-Fi, and LiFi, Powered by Artificial Intelligence and Intent Based Policy (5G-CLARITY)". It started on Nov. 2019 and it will end on April 2022. The main web page of this project is available at https://www.5gclarity.com/

Description

    5G-CLARITY will develop and demonstrate a beyond 5G system for private networks integrating 5G, Wi-Fi, and LiFi technologies, and managed through AI based autonomic networking.
    The first pillar of this project is a heterogeneous wireless access network that integrates three technologies: 5G beyond R16, Wi-Fi, and LiFi.
    The second pillar of our vision is a novel management plane based on the principles of Software Defined Networking (SDN) and Network Function Virtualization (NFV), and powered by Artificial Intelligence (AI) algorithms, in order to enable network slicing for neutral hosts, and autonomic network management.
    This project is developed by a consortium of companies (including world-leading manufacturers and operators), research centres and universities: IHP, Ericsson, InterDigital, i2CAT, Gigasys Solutions, pureLiFi, Bosch, Accelleran, Telefonica R&D, University of Edinburgh, Universidad de Granada and University of Bristol.

Testbeds and repositories

5G-Clarity Testbed v0

    Testbed v0 (virtualized environment) for the 5G-CLARITY European Project. Available here.
    The following picture summarizes one of the scenarios, where the CPE (VM mptcpUe) is connected using 3 network interfaces (5G NR, Wi-Fi and Li-Fi) to the MPTCP proxy (VM mptcpProxy) through the Non-3GPP Interworking Function (N3IWF) of a 5G Core Network (implemented using free5gc).
    Testbed v0 (scenario with free5gc)

    The following picture summarizes another scenario, where the CPE is connected to several MPTCP proxies. The CPE acts as a switch (using OVS) for all the clients that may be connected, and uses different VLAN IDs to route the packets to the server through the different proxies (one VLAN per proxy).
    Testbed v0 (scenario with OVS)
    You can check the following video with the execution of this testbed. Available here. Please download the video before watching (it may not play directly on the browser).

Linux kernel 5.5 with MPTCP support

    Linux kernel 5.5 with MPTCP support. Available here, for both x86-64 (PC) and ARMv8 (Raspberry Pi 4) architectures.

Thesis

Related ongoing Ph.D. thesis

  1. Orchestration and management of independent virtualized networks for the support of new services in 5G
    Jose Antonio Ordonez-Lucena (directed by Pablo Ameigeiras)
    Defended on October 2022.
    "Orchestration and management of independent virtualized networks for the support of new services in 5G", Jose Antonio Ordonez-Lucena, University of Granada, 2022
    close
    @PhdThesis{thesisordonez,
      author      = {Jose Antonio Ordonez-Lucena},
      director    = {Pablo Ameigeiras},
      title       = {Orchestration and management of independent virtualized networks for the support of new services in 5G},
      institution = {University of Granada},
      type        = {phdthesis},
      project     = {5gcity|5gclarity|true5g|6gchronos},
      year        = {2022},
      month       = {October},
      pagetotal   = {321}
    }
    close

  2. Network Slicing Management for 5G Radio Access Networks
    Oscar Adamuz-Hinojosa (directed by Pablo Ameigeiras and Juan M. Lopez-Soler)
    Defended on April 2022, ISBN 9788411173377.
    "Network Slicing Management for 5G Radio Access Networks", Oscar Adamuz-Hinojosa, University of Granada, ISBN 9788411173377, 2022
    close
    @PhdThesis{thesisadamuz,
      author      = {Oscar Adamuz-Hinojosa},
      director    = {Pablo Ameigeiras and Juan M. Lopez-Soler},
      title       = {Network Slicing Management for 5G Radio Access Networks},
      institution = {University of Granada},
      type        = {phdthesis},
      project     = {5gcity|5gclarity|true5g|6gchronos},
      year        = {2022},
      type        = {phdthesis},
      language    = {English},
      month       = {April},
      isbn        = {9788411173377},
      pagetotal   = {380},
      pdf         = {https://digibug.ugr.es/bitstream/handle/10481/74957/80783%281%29.pdf}
    
    }
    close

  3. Multi-connectivity solutions for 5G/6G networks
    Felix Delgado-Ferro (directed by Jorge Navarro-Ortiz and Juan M. Lopez-Soler)
    Ongoing.
    "Multi-connectivity solutions for 5G/6G networks", Felix Delgado-Ferro, University of Granada
    close
    @PhdThesis{thesisdelgado,
      author      = {Felix Delgado-Ferro},
      director    = {Jorge Navarro-Ortiz and Juan M. Lopez-Soler},
      title       = {Multi-connectivity solutions for 5G/6G networks},
      institution = {University of Granada},
      type        = {phdthesis},
      project     = {5gclarity|true5g|artemis|premonition|6gchronos},
      note        = "ongoing"
    }
    close

  4. AI-assisted management of 5G private networks
    Lorena Chinchilla-Romero (directed by Pablo Ameigeiras and Pablo Muñoz)
    Ongoing.
    "AI-assisted management of 5G private networks", Lorena Chinchilla-Romero, University of Granada
    close
    @PhdThesis{thesislorena,
      author      = {Lorena Chinchilla-Romero},
      director    = {Pablo Ameigeiras and Pablo Muñoz},
      title       = {AI-assisted management of 5G private networks},
      institution = {University of Granada},
      type        = {phdthesis},
      project     = {5gclarity|true5g|6gchronos},
      note        = "ongoing"
    }
    close

  5. Optimization and orchestration of LoRaWAN networks
    Natalia Chinchilla-Romero (directed by Jorge Navarro-Ortiz)
    Ongoing.
    "Optimization and orchestration of LoRaWAN networks", Natalia Chinchilla-Romero, University of Granada
    close
    @PhdThesis{thesisnatalia,
      author      = {Natalia Chinchilla-Romero},
      director    = {Jorge Navarro-Ortiz},
      title       = {Optimization and orchestration of LoRaWAN networks},
      institution = {University of Granada},
      type        = {phdthesis},
      project     = {5gclarity|true5g|artemis|premonition|6gchronos},
      note        = "ongoing"
    }
    close


Related B.Sc. and M.Sc. thesis

  1. Configuration and performance assessment of 4G/5G networks
    M.Sc. thesis (M.Sc. Telecommunications Engineering)
    Felix Delgado-Ferro
    Defended on July 2022.
    "Configuration and performance assessment of 4G/5G networks", Felix Delgado-Ferro, 2022
    close
    @mastersthesis{delgado_2022,
      author       = {Felix Delgado-Ferro},
      title        = {Configuration and performance assessment of 4G/5G networks},
      school       = {Higher Technical School of Informatics and Telecommunications, University of Granada},
      type         = {M.Sc. thesis},
      degree       = {M.Sc. Telecommunications Engineering},
      year         = 2022,
      month        = July,
      pdf          = {https://wpd.ugr.es/~jorgenavarro/thesis/2022_TFM_FelixDelgadoFerro.pdf},
      project      = {6gchronos|true5g|5gclarity},
      note         = {This thesis obtained the maximum possible mark.}
    }
    close


Publications

Journals

  1. 5G-CLARITY: 5G-Advanced Private Networks Integrating 5GNR, WiFi, and LiFi
    Tezcan Cogalan, Daniel Camps-Mur, Jesús Gutiérrez, Stefan Videv, Vladica Sark, Jonathan Prados-Garzon, Jose Ordonez-Lucena, Hamzeh Khalili, Ferran Cañellas, Adriana Fernández-Fernández, Meysam Goodarzi, Anil Yesilkaya, Rui Bian, Srinivasan Raju, Mir Ghoraishi, Harald Haas, Oscar Adamuz-Hinojosa, Antonio Garcia, Carlos Colman-Meixner, Alain Mourad, Erik Aumayr
    IEEE Communications Magazine, 60 (2), pp. 73-79, 2022, DOI: 10.1109/MCOM.001.2100615. (IF = 9.619, Q1)
    "5G-CLARITY: 5G-Advanced Private Networks Integrating 5GNR, WiFi, and LiFi", Tezcan Cogalan, Daniel Camps-Mur, Jesús Gutiérrez, Stefan Videv, Vladica Sark, Jonathan Prados-Garzon, Jose Ordonez-Lucena, Hamzeh Khalili, Ferran Cañellas, Adriana Fernández-Fernández, Meysam Goodarzi, Anil Yesilkaya, Rui Bian, Srinivasan Raju, Mir Ghoraishi, Harald Haas, Oscar Adamuz-Hinojosa, Antonio Garcia, Carlos Colman-Meixner, Alain Mourad, Erik Aumayr, IEEE Communications Magazine, 60 (2), pp. 73-79, 2022. DOI: 10.1109/MCOM.001.2100615
    close
    @ARTICLE{9722800,
       author={Cogalan, Tezcan and Camps-Mur, Daniel and Gutiérrez, Jesús and Videv, Stefan and Sark, Vladica and Prados-Garzon, Jonathan and Ordonez-Lucena, Jose and Khalili, Hamzeh and Cañellas, Ferran and Fernández-Fernández, Adriana and Goodarzi, Meysam and Yesilkaya, Anil and Bian, Rui and Raju, Srinivasan and Ghoraishi, Mir and Haas, Harald and Adamuz-Hinojosa, Oscar and Garcia, Antonio and Colman-Meixner, Carlos and Mourad, Alain and Aumayr, Erik}, journal={IEEE Communications Magazine},
       title={5G-CLARITY: 5G-Advanced Private Networks Integrating 5GNR, WiFi, and LiFi},
       year={2022},
       volume={60},
       number={2},
       pages={73-79},
       doi={10.1109/MCOM.001.2100615},
       project={5gclarity},
       impact = {(IF = 9.619, Q1)}
    }
    close

  2. 5G Infrastructure Network Slicing: E2E Mean Delay Model and Effectiveness Assessment to Reduce Downtimes in Industry 4.0
    Lorena Chinchilla-Romero, Jonathan Prados-Garzon, Pablo Ameigeiras, Pablo Muñoz, Juan M. Lopez-Soler
    Sensors, 22 (1), 2022, DOI: 10.3390/s22010229. (IF = 3.275, Q1)
    "5G Infrastructure Network Slicing: E2E Mean Delay Model and Effectiveness Assessment to Reduce Downtimes in Industry 4.0", Lorena Chinchilla-Romero, Jonathan Prados-Garzon, Pablo Ameigeiras, Pablo Muñoz, Juan M. Lopez-Soler, Sensors, 22 (1), 2022. DOI: 10.3390/s22010229
    close
    Fifth Generation (5G) is expected to meet stringent performance network requisites of the Industry 4.0. Moreover, its built-in network slicing capabilities allow for the support of the traffic heterogeneity in Industry 4.0 over the same physical network infrastructure. However, 5G network slicing capabilities might not be enough in terms of degree of isolation for many private 5G networks use cases, such as multi-tenancy in Industry 4.0. In this vein, infrastructure network slicing, which refers to the use of dedicated and well isolated resources for each network slice at every network domain, fits the necessities of those use cases. In this article, we evaluate the effectiveness of infrastructure slicing to provide isolation among production lines (PLs) in an industrial private 5G network. To that end, we develop a queuing theory-based model to estimate the end-to-end (E2E) mean packet delay of the infrastructure slices. Then, we use this model to compare the E2E mean delay for two configurations, i.e., dedicated infrastructure slices with segregated resources for each PL against the use of a single shared infrastructure slice to serve the performance-sensitive traffic from PLs. Also we evaluate the use of Time-Sensitive Networking (TSN) against bare Ethernet to provide layer 2 connectivity among the 5G system components. We use a complete and realistic setup based on experimental and simulation data of the scenario considered. Our results support the effectiveness of infrastructure slicing to provide isolation in performance among the different slices. Then, using dedicated slices with segregated resources for each PL might reduce the number of the production downtimes and associated costs as the malfunctioning of a PL will not affect the network performance perceived by the performance-sensitive traffic from other PLs. Last, our results show that, besides the improvement in performance, TSN technology truly provides full isolation in the transport network compared to standard Ethernet thanks to traffic prioritization, traffic regulation, and bandwidth reservation capabilities.
    close
    @Article{s22010229,
    AUTHOR = {Chinchilla-Romero, Lorena and Prados-Garzon, Jonathan and Ameigeiras, Pablo and Muñoz, Pablo and Lopez-Soler, Juan M.},
    TITLE = {5G Infrastructure Network Slicing: E2E Mean Delay Model and Effectiveness Assessment to Reduce Downtimes in Industry 4.0},
    JOURNAL = {Sensors},
    VOLUME = {22},
    YEAR = {2022},
    NUMBER = {1},
    ARTICLE-NUMBER = {229},
    URL = {https://www.mdpi.com/1424-8220/22/1/229},
    PubMedID = {35009771},
    ISSN = {1424-8220},
    ABSTRACT = {Fifth Generation (5G) is expected to meet stringent performance network requisites of the Industry 4.0. Moreover, its built-in network slicing capabilities allow for the support of the traffic heterogeneity in Industry 4.0 over the same physical network infrastructure. However, 5G network slicing capabilities might not be enough in terms of degree of isolation for many private 5G networks use cases, such as multi-tenancy in Industry 4.0. In this vein, infrastructure network slicing, which refers to the use of dedicated and well isolated resources for each network slice at every network domain, fits the necessities of those use cases. In this article, we evaluate the effectiveness of infrastructure slicing to provide isolation among production lines (PLs) in an industrial private 5G network. To that end, we develop a queuing theory-based model to estimate the end-to-end (E2E) mean packet delay of the infrastructure slices. Then, we use this model to compare the E2E mean delay for two configurations, i.e., dedicated infrastructure slices with segregated resources for each PL against the use of a single shared infrastructure slice to serve the performance-sensitive traffic from PLs. Also we evaluate the use of Time-Sensitive Networking (TSN) against bare Ethernet to provide layer 2 connectivity among the 5G system components. We use a complete and realistic setup based on experimental and simulation data of the scenario considered. Our results support the effectiveness of infrastructure slicing to provide isolation in performance among the different slices. Then, using dedicated slices with segregated resources for each PL might reduce the number of the production downtimes and associated costs as the malfunctioning of a PL will not affect the network performance perceived by the performance-sensitive traffic from other PLs. Last, our results show that, besides the improvement in performance, TSN technology truly provides full isolation in the transport network compared to standard Ethernet thanks to traffic prioritization, traffic regulation, and bandwidth reservation capabilities.},
    DOI = {10.3390/s22010229},
    project={5gclarity|true5g},
    impact={(IF = 3.275, Q1)}
    }
    close

  3. On the Rollout of Network Slicing in Carrier Networks: A Technology Radar
    Jose Ordonez-Lucena, Pablo Ameigeiras, Luis M. Contreras, Jesús Folgueira, Diego R. López
    Sensors, 21 (23), 12 2021, DOI: 10.3390/s21238094. (IF=3.275, Q1)
    "On the Rollout of Network Slicing in Carrier Networks: A Technology Radar", Jose Ordonez-Lucena, Pablo Ameigeiras, Luis M. Contreras, Jesús Folgueira, Diego R. López, Sensors, 21 (23), 2021. DOI: 10.3390/s21238094
    close
    Network slicing is a powerful paradigm for network operators to support use cases with widely diverse requirements atop a common infrastructure. As 5G standards are completed, and commercial solutions mature, operators need to start thinking about how to integrate network slicing capabilities in their assets, so that customer-facing solutions can be made available in their portfolio. This integration is, however, not an easy task, due to the heterogeneity of assets that typically exist in carrier networks. In this regard, 5G commercial networks may consist of a number of domains, each with a different technological pace, and built out of products from multiple vendors, including legacy network devices and functions. These multi-technology, multi-vendor and brownfield features constitute a challenge for the operator, which is required to deploy and operate slices across all these domains in order to satisfy the end-to-end nature of the services hosted by these slices. In this context, the only realistic option for operators is to introduce slicing capabilities progressively, following a phased approach in their roll-out. The purpose of this paper is to precisely help designing this kind of plan, by means of a technology radar. The radar identifies a set of solutions enabling network slicing on the individual domains, and classifies these solutions into four rings, each corresponding to a different timeline: (i) as-is ring, covering today’s slicing solutions; (ii) deploy ring, corresponding to solutions available in the short term; (iii) test ring, considering medium-term solutions; and (iv) explore ring, with solutions expected in the long run. This classification is done based on the technical availability of the solutions, together with the foreseen market demands. The value of this radar lies in its ability to provide a complete view of the slicing landscape with one single snapshot, by linking solutions to information that operators may use for decision making in their individual go-to-market strategies.
    close
    @Article{s21238094,
    AUTHOR = {Ordonez-Lucena, Jose and Ameigeiras, Pablo and Contreras, Luis M. and Folgueira, Jesús and López, Diego R.},
    TITLE = {On the Rollout of Network Slicing in Carrier Networks: A Technology Radar},
    JOURNAL = {Sensors},
    VOLUME = {21},
    YEAR = {2021},
    month = {12},
    NUMBER = {23},
    ARTICLE-NUMBER = {8094},
    URL = {https://www.mdpi.com/1424-8220/21/23/8094},
    PubMedID = {34884098},
    ISSN = {1424-8220},
    ABSTRACT = {Network slicing is a powerful paradigm for network operators to support use cases with widely diverse requirements atop a common infrastructure. As 5G standards are completed, and commercial solutions mature, operators need to start thinking about how to integrate network slicing capabilities in their assets, so that customer-facing solutions can be made available in their portfolio. This integration is, however, not an easy task, due to the heterogeneity of assets that typically exist in carrier networks. In this regard, 5G commercial networks may consist of a number of domains, each with a different technological pace, and built out of products from multiple vendors, including legacy network devices and functions. These multi-technology, multi-vendor and brownfield features constitute a challenge for the operator, which is required to deploy and operate slices across all these domains in order to satisfy the end-to-end nature of the services hosted by these slices. In this context, the only realistic option for operators is to introduce slicing capabilities progressively, following a phased approach in their roll-out. The purpose of this paper is to precisely help designing this kind of plan, by means of a technology radar. The radar identifies a set of solutions enabling network slicing on the individual domains, and classifies these solutions into four rings, each corresponding to a different timeline: (i) as-is ring, covering today’s slicing solutions; (ii) deploy ring, corresponding to solutions available in the short term; (iii) test ring, considering medium-term solutions; and (iv) explore ring, with solutions expected in the long run. This classification is done based on the technical availability of the solutions, together with the foreseen market demands. The value of this radar lies in its ability to provide a complete view of the slicing landscape with one single snapshot, by linking solutions to information that operators may use for decision making in their individual go-to-market strategies.},
    DOI = {10.3390/s21238094},
    project={5gclarity|true5g},
    impact = {(IF=3.275, Q1)}
    }
    close

  4. 5G Non-Public Networks: Standardization, Architectures and Challenges
    Jonathan Prados-Garzon, Pablo Ameigeiras, Jose Ordonez-Lucena, Pablo Muñoz, Oscar Adamuz-Hinojosa, Daniel Camps-Mur
    IEEE Access, 9, pp. 153893-153908, 11 2021, DOI: 10.1109/ACCESS.2021.3127482. (IF = 3.367, Q2)
    "5G Non-Public Networks: Standardization, Architectures and Challenges", Jonathan Prados-Garzon, Pablo Ameigeiras, Jose Ordonez-Lucena, Pablo Muñoz, Oscar Adamuz-Hinojosa, Daniel Camps-Mur, IEEE Access, 9, pp. 153893-153908, 2021. DOI: 10.1109/ACCESS.2021.3127482
    close
    @ARTICLE{9611236,
       author={Prados-Garzon, Jonathan and Ameigeiras, Pablo and Ordonez-Lucena, Jose and Muñoz, Pablo and Adamuz-Hinojosa, Oscar and Camps-Mur, Daniel},
       journal={IEEE Access},
       title="5G Non-Public Networks: Standardization, Architectures and Challenges",
       year={2021},
       month={11},
       volume={9},
       number={},
       pages={153893-153908},
       doi={10.1109/ACCESS.2021.3127482},
       project={5gclarity|true5g},
       impact = {(IF = 3.367, Q2)}
    }
    close

  5. Deep Reinforcement Learning based Collision Avoidance in UAV Environment
    Sihem Ouahouah, Miloud Bagaa, Jonathan Prados-Garzon, Tarik Taleb
    IEEE Internet of Things Journal, pp. 1-1, 10 2021, DOI: 10.1109/JIOT.2021.3118949. (IF = 9.471, Q1)
    "Deep Reinforcement Learning based Collision Avoidance in UAV Environment", Sihem Ouahouah, Miloud Bagaa, Jonathan Prados-Garzon, Tarik Taleb, IEEE Internet of Things Journal, pp. 1-1, 2021. DOI: 10.1109/JIOT.2021.3118949
    close
    @ARTICLE{9564258,
       author={Ouahouah, Sihem and Bagaa, Miloud and Prados-Garzon, Jonathan and Taleb, Tarik},
       journal={IEEE Internet of Things Journal},
       title={Deep Reinforcement Learning based Collision Avoidance in UAV Environment},
       year={2021},
       month=10,
       volume={},
       number={},
       pages={1-1},
       doi={10.1109/JIOT.2021.3118949},
       project={5gclarity|true5g},
       impact = {(IF = 9.471, Q1)}}
    close

  6. Asynchronous Time-Sensitive Networking for 5G Backhauling
    J. Prados-Garzon, T. Taleb
    IEEE Network, 35 (2), pp. 144-151, March 2021, DOI: 10.1109/MNET.011.2000402. (IF = 10.234, Q1)
    "Asynchronous Time-Sensitive Networking for 5G Backhauling", J. Prados-Garzon, T. Taleb, IEEE Network, 35 (2), pp. 144-151, 2021. DOI: 10.1109/MNET.011.2000402
    close
    Fifth Generation (5G) phase 2 rollouts are around the corner to make mobile ultra-reliable and low-latency services a reality. However, to realize that scenario, besides the new 5G built-in Ultra-Reliable Low-Latency Communication (URLLC) capabilities, it is required to provide a substrate network with deterministic Quality-of-Service support for interconnecting the different 5G network functions and services. Time-Sensitive Networking (TSN) appears as an appealing network technology to meet the 5G connectivity needs in many scenarios involving critical services and their coexistence with Mobile Broadband traffic. In this article, we delve into the adoption of asynchronous TSN for 5G backhauling and some of the relevant related aspects. We start motivating TSN and introducing its mainstays. Then, we provide a comprehensive overview of the architecture and operation of the Asynchronous Traffic Shaper (ATS), the building block of asynchronous TSN. Next, a management framework based on ETSI Zero-touch network and Service Management (ZSM) and Abstraction and Control of Traffic Engineered Networks (ACTN) reference models is presented for enabling the TSN transport network slicing and its interworking with Fifth Generation (5G) for backhauling. Then we cover the flow allocation problem in asynchronous TSNs and the importance of Machine Learning techniques for assisting it. Last, we present a simulation-based proof-of-concept (PoC) to assess the capacity of ATS-based forwarding planes for accommodating 5G data flows.
    close
    @ARTICLE{9373015,  author={J. {Prados-Garzon} and T. {Taleb}},  journal={IEEE Network},   title={Asynchronous Time-Sensitive Networking for 5G Backhauling}, year={2021},  volume={35},  number={2},  pages={144-151},  abstract={Fifth Generation (5G) phase 2 rollouts are around the corner to make mobile ultra-reliable and low-latency services a reality. However, to realize that scenario, besides the new 5G built-in Ultra-Reliable Low-Latency Communication (URLLC) capabilities, it is required to provide a substrate network with deterministic Quality-of-Service support for interconnecting the different 5G network functions and services. Time-Sensitive Networking (TSN) appears as an appealing network technology to meet the 5G connectivity needs in many scenarios involving critical services and their coexistence with Mobile Broadband traffic. In this article, we delve into the adoption of asynchronous TSN for 5G backhauling and some of the relevant related aspects. We start motivating TSN and introducing its mainstays. Then, we provide a comprehensive overview of the architecture and operation of the Asynchronous Traffic Shaper (ATS), the building block of asynchronous TSN. Next, a management framework based on ETSI Zero-touch network and Service Management (ZSM) and Abstraction and Control of Traffic Engineered Networks (ACTN) reference models is presented for enabling the TSN transport network slicing and its interworking with Fifth Generation (5G) for backhauling. Then we cover the flow allocation problem in asynchronous TSNs and the importance of Machine Learning techniques for assisting it. Last, we present a simulation-based proof-of-concept (PoC) to assess the capacity of ATS-based forwarding planes for accommodating 5G data flows.},  keywords={5G mobile communication;Logic gates;Resource management;Regulation;Substrates;Bridges;Ultra reliable low latency communication;Machine learning;Network slicing;Broadband communication},  doi={10.1109/MNET.011.2000402},  ISSN={1558-156X},  month={March},
    project={5gclarity|true5g},impact = {(IF = 10.234, Q1)}
    }
    close

  7. Collision Avoidance Resource Allocation for LoRaWAN
    Natalia Chinchilla-Romero, Jorge Navarro-Ortiz, Pablo Muñoz, Pablo Ameigeiras
    Sensors, 21 (4), 2 2021, DOI: 10.3390/s21041218. (IF=3.275, Q1)
    "Collision Avoidance Resource Allocation for LoRaWAN", Natalia Chinchilla-Romero, Jorge Navarro-Ortiz, Pablo Muñoz, Pablo Ameigeiras, Sensors, 21 (4), 2021. DOI: 10.3390/s21041218
    close
    The number of connected IoT devices is significantly increasing and it is expected to reach more than two dozens of billions of IoT connections in the coming years. Low Power Wide Area Networks (LPWAN) have become very relevant for this new paradigm due to features such as large coverage and low power consumption. One of the most appealing technologies among these networks is LoRaWAN. Although it may be considered as one of the most mature LPWAN platforms, there are still open gaps such as its capacity limitations. For this reason, this work proposes a collision avoidance resource allocation algorithm named the Collision Avoidance Resource Allocation (CARA) algorithm with the objective of significantly increase system capacity. CARA leverages the multichannel structure and the orthogonality of spreading factors in LoRaWAN networks to avoid collisions among devices. Simulation results show that, assuming ideal radio link conditions, our proposal outperforms in 95.2% the capacity of a standard LoRaWAN network and increases the capacity by almost 40% assuming a realistic propagation model. In addition, it has been verified that CARA devices can coexist with LoRaWAN traditional devices, thus allowing the simultaneous transmissions of both types of devices. Moreover, a proof-of-concept has been implemented using commercial equipment in order to check the feasibility and the correct operation of our solution.
    close
    @ARTICLE{s21041218,
    AUTHOR = {Chinchilla-Romero, Natalia and Navarro-Ortiz, Jorge and Muñoz, Pablo and Ameigeiras, Pablo},
    TITLE = {Collision Avoidance Resource Allocation for {LoRaWAN}},
    JOURNAL = {Sensors},
    VOLUME = {21},
    YEAR = {2021},
    month=2,
    NUMBER = {4},
    ARTICLE-NUMBER = {1218},
    ISSN = {1424-8220},
    ABSTRACT = {The number of connected IoT devices is significantly increasing and it is expected to reach more than two dozens of billions of IoT connections in the coming years. Low Power Wide Area Networks (LPWAN) have become very relevant for this new paradigm due to features such as large coverage and low power consumption. One of the most appealing technologies among these networks is {LoRaWAN}. Although it may be considered as one of the most mature LPWAN platforms, there are still open gaps such as its capacity limitations. For this reason, this work proposes a collision avoidance resource allocation algorithm named the Collision Avoidance Resource Allocation (CARA) algorithm with the objective of significantly increase system capacity. CARA leverages the multichannel structure and the orthogonality of spreading factors in {LoRaWAN} networks to avoid collisions among devices. Simulation results show that, assuming ideal radio link conditions, our proposal outperforms in 95.2% the capacity of a standard {LoRaWAN} network and increases the capacity by almost 40% assuming a realistic propagation model. In addition, it has been verified that CARA devices can coexist with {LoRaWAN} traditional devices, thus allowing the simultaneous transmissions of both types of devices. Moreover, a proof-of-concept has been implemented using commercial equipment in order to check the feasibility and the correct operation of our solution.},
    DOI = {10.3390/s21041218},
    impact = {(IF=3.275, Q1)},
    pdf = {https://digibug.ugr.es/handle/10481/67701},
    project = {artemis|5gcity|5gclarity}
    }
    close

  8. Optimization of Flow Allocation in Asynchronous Deterministic 5G Transport Networks by Leveraging Data Analytics
    Jonathan Prados-Garzon, Tarik Taleb, Miloud Bagaa
    IEEE Transactions on Mobile Computing, pp. 1-1, 7 2021, DOI: 10.1109/TMC.2021.3099979. (IF = 5.577, Q1)
    "Optimization of Flow Allocation in Asynchronous Deterministic 5G Transport Networks by Leveraging Data Analytics", Jonathan Prados-Garzon, Tarik Taleb, Miloud Bagaa, IEEE Transactions on Mobile Computing, pp. 1-1, 2021. DOI: 10.1109/TMC.2021.3099979
    close
    @ARTICLE{9496182,
      author={Prados-Garzon, Jonathan and Taleb, Tarik and Bagaa, Miloud},
      journal={IEEE Transactions on Mobile Computing},
      title={Optimization of Flow Allocation in Asynchronous Deterministic 5G Transport Networks by Leveraging Data Analytics},
      year={2021},
      month=7,
      volume={},
      number={},
      pages={1-1},
      doi={10.1109/TMC.2021.3099979},
      project={5gclarity|true5g},impact = {(IF = 5.577, Q1)}
      }
    close

  9. A Survey on 5G Usage Scenarios and Traffic Models
    J. Navarro-Ortiz, P. Romero-Diaz, S. Sendra, P. Ameigeiras, J. J. Ramos-Munoz, J. M. Lopez-Soler
    IEEE Communications Surveys Tutorials, 22 (2), pp. 905-929, 2 2020, DOI: 10.1109/COMST.2020.2971781. (IF=23.7, Q1)
    "A Survey on 5G Usage Scenarios and Traffic Models", J. Navarro-Ortiz, P. Romero-Diaz, S. Sendra, P. Ameigeiras, J. J. Ramos-Munoz, J. M. Lopez-Soler, IEEE Communications Surveys Tutorials, 22 (2), pp. 905-929, 2020. DOI: 10.1109/COMST.2020.2971781
    close
    @Article{8985528,  author={J. {Navarro-Ortiz} and P. {Romero-Diaz} and S. {Sendra} and P. {Ameigeiras} and J. J. {Ramos-Munoz} and J. M. {Lopez-Soler}},  journal={{IEEE} Communications Surveys Tutorials}, title={A Survey on 5G Usage Scenarios and Traffic Models}, year={2020}, month=2, volume={22}, number={2}, pages={905-929}, doi={10.1109/COMST.2020.2971781}, project="artemis|5gclarity|5gcity", impact = {(IF=23.7, Q1)}, pdf={https://digibug.ugr.es/handle/10481/59687}}
    close

  10. Radio Access Network Slicing Strategies at Spectrum Planning Level in 5G and Beyond
    P. Muñoz, O. Adamuz-Hinojosa, J. Navarro-Ortiz, O. Sallent, J. Pérez-Romero
    IEEE Access, 8, pp. 79604-79618, 4 2020, DOI: 10.1109/ACCESS.2020.2990802. (IF=3.745, Q1)
    "Radio Access Network Slicing Strategies at Spectrum Planning Level in 5G and Beyond", P. Muñoz, O. Adamuz-Hinojosa, J. Navarro-Ortiz, O. Sallent, J. Pérez-Romero, IEEE Access, 8, pp. 79604-79618, 2020. DOI: 10.1109/ACCESS.2020.2990802
    close
    @Article{9079548,  author={P. {Muñoz} and O. {Adamuz-Hinojosa} and J. {Navarro-Ortiz} and O. {Sallent} and J. {Pérez-Romero}},  journal={{IEEE} Access},   title={Radio Access Network Slicing Strategies at Spectrum Planning Level in 5G and Beyond}, year={2020}, month=4,  volume={8},  number={},  pages={79604-79618},  doi={10.1109/ACCESS.2020.2990802}, project="5gclarity|artemis", impact = {(IF=3.745, Q1)}}
    close

  11. Backhaul-Aware Dimensioning and Planning of Millimeter-Wave Small Cell Networks
    Pablo Muñoz, Oscar Adamuz-Hinojosa, Pablo Ameigeiras, Jorge Navarro-Ortiz, Juan J. Ramos-Muñoz
    Electronics, 9 (9), 9 2020, DOI: 10.3390/electronics9091429. (IF=2.397, Q3)
    "Backhaul-Aware Dimensioning and Planning of Millimeter-Wave Small Cell Networks", Pablo Muñoz, Oscar Adamuz-Hinojosa, Pablo Ameigeiras, Jorge Navarro-Ortiz, Juan J. Ramos-Muñoz, Electronics, 9 (9), 2020. DOI: 10.3390/electronics9091429
    close
    The massive deployment of Small Cells (SCs) is increasingly being adopted by mobile operators to face the exponentially growing traffic demand. Using the millimeter-wave (mmWave) band in the access and backhaul networks will be key to provide the capacity that meets such demand. However, dimensioning and planning have become complex tasks, because the capacity requirements for mmWave links can significantly vary with the SC location. In this work, we address the problem of SC planning considering the backhaul constraints, assuming that a line-of-sight (LOS) between the nodes is required to reliably support the traffic demand. Such a LOS condition reduces the set of potential site locations. Simulation results show that, under certain conditions, the proposed algorithm is effective in finding solutions and strongly efficient in computational cost when compared to exhaustive search approaches.
    close
    @article{electronics9091429,
    AUTHOR = {Muñoz, Pablo and Adamuz-Hinojosa, Oscar and Ameigeiras, Pablo and Navarro-Ortiz, Jorge and Ramos-Muñoz, Juan J.},
    TITLE = {Backhaul-Aware Dimensioning and Planning of Millimeter-Wave Small Cell Networks},
    JOURNAL = {Electronics},
    VOLUME = {9},
    YEAR = {2020},
    month=9,
    NUMBER = {9},
    ARTICLE-NUMBER = {1429},
    ISSN = {2079-9292},
    ABSTRACT = {The massive deployment of Small Cells (SCs) is increasingly being adopted by mobile operators to face the exponentially growing traffic demand. Using the millimeter-wave (mmWave) band in the access and backhaul networks will be key to provide the capacity that meets such demand. However, dimensioning and planning have become complex tasks, because the capacity requirements for mmWave links can significantly vary with the SC location. In this work, we address the problem of SC planning considering the backhaul constraints, assuming that a line-of-sight (LOS) between the nodes is required to reliably support the traffic demand. Such a LOS condition reduces the set of potential site locations. Simulation results show that, under certain conditions, the proposed algorithm is effective in finding solutions and strongly efficient in computational cost when compared to exhaustive search approaches.},
    DOI = {10.3390/electronics9091429},
    impact = {(IF=2.397, Q3)},
    project = {5gclarity|true5g}
    }
    close

  12. Performance Modeling of Softwarized Network Services Based on Queuing Theory With Experimental Validation
    J. Prados-Garzon, P. Ameigeiras, J. J. Ramos-Munoz, J. Navarro-Ortiz, P. Andres-Maldonado, J. M. Lopez-Soler
    IEEE Transactions on Mobile Computing, 20 (4), pp. 1558-1573, 12 2019, DOI: 10.1109/TMC.2019.2962488. (IF=5.112, Q1)
    "Performance Modeling of Softwarized Network Services Based on Queuing Theory With Experimental Validation", J. Prados-Garzon, P. Ameigeiras, J. J. Ramos-Munoz, J. Navarro-Ortiz, P. Andres-Maldonado, J. M. Lopez-Soler, IEEE Transactions on Mobile Computing, 20 (4), pp. 1558-1573, 2019. DOI: 10.1109/TMC.2019.2962488
    close
    @Article{8943161,  author={J. {Prados-Garzon} and P. {Ameigeiras} and J. J. {Ramos-Munoz} and J. {Navarro-Ortiz} and P. {Andres-Maldonado} and J. M. {Lopez-Soler}},  journal={{IEEE} Transactions on Mobile Computing},   title={Performance Modeling of Softwarized Network Services Based on Queuing Theory With Experimental Validation},   year={2019}, month={12},  volume={20},  number={4},  pages={1558-1573},  doi={10.1109/TMC.2019.2962488}, project="5gclarity|5gcity", impact={(IF=5.112, Q1)}, pdf={https://digibug.ugr.es/handle/10481/59700}}
    close


Conferences & Workshops

  1. Analytical Model for the UE Blocking Probability in an OFDMA Cell providing GBR Slices
    O. Adamuz-Hinojosa, P. Ameigeiras, P. Munoz, J. M. Lopez-Soler
    2021 IEEE Wireless Communications and Networking Conference (WCNC), Nanjing, China, pp. 1-7, Mar. 2021.
    "Analytical Model for the UE Blocking Probability in an OFDMA Cell providing GBR Slices", O. Adamuz-Hinojosa, P. Ameigeiras, P. Munoz, J. M. Lopez-Soler, "2021 IEEE Wireless Communications and Networking Conference (WCNC), Nanjing, China", pp. 1-7, 2021
    close
    When a network operator designs strategies for planning and operating Guaranteed Bit Rate (GBR) slices, there are inherent issues such as the under(over)-provisioning of radio resources. To avoid them, modeling the User Equipment (UE) blocking probability in each cell is key. This task is challenging due to the total required bandwidth depends on the channel quality of each UE and the spatio-temporal variations in the number of UE sessions. Under this context, we propose an analytical model to evaluate the UE blocking probability in an Orthogonal Frequency Division Multiple Access (OFDMA) cell. The main novelty of our model is the adoption of a multi-dimensional Erlang-B system which meets the reversibility property. This means our model is insensitive to the holding time distribution for the UE session. In addition, this property reduces the computational complexity of our model due to the solution for the state transition probabilities has product form. The provided results show that our model exhibits an estimation error for the UE blocking probability below 3.5%.
    close
    @INPROCEEDINGS{OscarCellModel2021,
    author={O. {Adamuz-Hinojosa} and P. {Ameigeiras} and P. {Munoz} and J. M. {Lopez-Soler} },
    booktitle={2021 IEEE Wireless Communications and Networking Conference (WCNC), Nanjing, China},
    title={Analytical Model for the UE Blocking Probability in an OFDMA Cell providing GBR Slices},
    year={2021},
    volume={},
    number={},
    pages={1-7},
    abstract={When a network operator designs strategies for planning and operating Guaranteed Bit Rate (GBR) slices, there are inherent issues such as the under(over)-provisioning of radio resources. To avoid them, modeling the User Equipment (UE) blocking probability in each cell is key. This task is challenging due to the total required bandwidth depends on the channel quality of each UE and the spatio-temporal variations in the number of UE sessions. Under this context, we propose an analytical model to evaluate the UE blocking probability in an Orthogonal Frequency Division Multiple Access (OFDMA) cell. The main novelty of our model is the adoption of a multi-dimensional Erlang-B system which meets the reversibility property. This means our model is insensitive to the holding time distribution for the UE session. In addition, this property reduces the computational complexity of our model due to the solution for the state transition probabilities has product form. The provided results show that our model exhibits an estimation error for the UE blocking probability below 3.5%.},
    keywords={Blocking probability; OFDMA; GBR; Erlang-B},
    doi={},
    ISSN={},
    month={Mar.},
    project={5gclarity|true5g}
    }
    close

  2. WiMuNet's research lines
    J. Navarro-Ortiz, N. Chinchilla-Romero, L. Chinchilla-Romero, J. Prados-Garzon, F. Delgado-Ferro, P. Ameigeiras, P. Munoz-Luengo, J. J. Ramos-Munoz, J. M. Lopez-Soler
    VI Workshop on QoE, QoS on Multimedia Communications (QQCM'21), 2021.
    "WiMuNet's research lines", J. Navarro-Ortiz, N. Chinchilla-Romero, L. Chinchilla-Romero, J. Prados-Garzon, F. Delgado-Ferro, P. Ameigeiras, P. Munoz-Luengo, J. J. Ramos-Munoz, J. M. Lopez-Soler, "VI Workshop on QoE, QoS on Multimedia Communications (QQCM'21)", ISBN 9788409311248, 2021
    close
    @Inproceedings{jnavarroqqcm21, author={J. {Navarro-Ortiz} and N. {Chinchilla-Romero} and L. {Chinchilla-Romero} and J. {Prados-Garzon} and F. {Delgado-Ferro} and P. {Ameigeiras} and P. {Munoz-Luengo} and J. J. {Ramos-Munoz} and J. M. {Lopez-Soler}}, booktitle={VI Workshop on QoE, QoS on Multimedia Communications (QQCM'21)}, isbn={9788409311248}, title={WiMuNet's research lines}, year={2021}, url={https://sites.google.com/unizar.es/qqcm-2021/agenda}, project={5gclarity|true5g|artemis}}
    close

  3. Arquitectura para redes IoT orientada a la sostenibilidad medioambiental (IoT network architecture for environmental sustainability)
    J. Navarro-Ortiz, N. Chinchilla-Romero, F. Delgado-Ferro, J.J. Ramos-Munoz
    XV Jornadas de Ingeniería Telemática (JITEL 2021), 2021.
    "Arquitectura para redes IoT orientada a la sostenibilidad medioambiental (IoT network architecture for environmental sustainability)", J. Navarro-Ortiz, N. Chinchilla-Romero, F. Delgado-Ferro, J.J. Ramos-Munoz, "XV Jornadas de Ingeniería Telemática (JITEL 2021)", 2021
    close
    @INPROCEEDINGS{jnavarro_jitel21,  author={J. {Navarro-Ortiz} and N. {Chinchilla-Romero} and F. {Delgado-Ferro} and J.J. {Ramos-Munoz}},  booktitle={XV Jornadas de Ingeniería Telemática (JITEL 2021)}, title={Arquitectura para redes IoT orientada a la sostenibilidad medioambiental (IoT network architecture for environmental sustainability)}, year={2021}, project = {5gclarity|true5g|artemis}, pdf={https://digibug.ugr.es/handle/10481/71142}}
    close

  4. Rendimiento de Redes 4G/5G usando una estación base real (Performance of 4G/5G networks using a real base station)
    F. Delgado-Ferro, J. Navarro-Ortiz, L. Chinchilla-Romero, P. Munoz-Luengo
    XV Jornadas de Ingeniería Telemática (JITEL 2021), 2021.
    "Rendimiento de Redes 4G/5G usando una estación base real (Performance of 4G/5G networks using a real base station)", F. Delgado-Ferro, J. Navarro-Ortiz, L. Chinchilla-Romero, P. Munoz-Luengo, "XV Jornadas de Ingeniería Telemática (JITEL 2021)", 2021
    close
    @INPROCEEDINGS{fdelgado_jitel21a,  author={F. {Delgado-Ferro} and J. {Navarro-Ortiz} and L. {Chinchilla-Romero} and P. {Munoz-Luengo}},  booktitle={XV Jornadas de Ingeniería Telemática (JITEL 2021)}, title={Rendimiento de Redes 4G/5G usando una estación base real (Performance of 4G/5G networks using a real base station)}, year={2021}, project = {5gclarity|true5g}, pdf={https://digibug.ugr.es/handle/10481/71140}}
    close

  5. Asynchronous Time-Sensitive Networking for Industrial Networks
    Jonathan Prados-Garzon, Lorena Chinchilla-Romero, Pablo Ameigeiras, Pablo Muñoz, Juan M. Lopez-Soler
    2021 Joint European Conference on Networks and Communications 6G Summit (EuCNC/6G Summit), pp. 130-135, 2021, DOI: 10.1109/EuCNC/6GSummit51104.2021.9482597.
    "Asynchronous Time-Sensitive Networking for Industrial Networks", Jonathan Prados-Garzon, Lorena Chinchilla-Romero, Pablo Ameigeiras, Pablo Muñoz, Juan M. Lopez-Soler, "2021 Joint European Conference on Networks and
    Communications   6G Summit (EuCNC/6G Summit)", pp. 130-135, 2021. DOI: 10.1109/EuCNC/6GSummit51104.2021.9482597
    close
    @INPROCEEDINGS{9482597,
       author={Prados-Garzon, Jonathan and Chinchilla-Romero, Lorena and Ameigeiras, Pablo and Muñoz, Pablo and Lopez-Soler, Juan M.},
       booktitle={2021 Joint European Conference on Networks and
    Communications   6G Summit (EuCNC/6G Summit)},
       title={Asynchronous Time-Sensitive Networking for Industrial Networks},
       year={2021},
       volume={},
       number={},
       pages={130-135},
       project={5gclarity|true5g},
       doi={10.1109/EuCNC/6GSummit51104.2021.9482597}}
    close

  6. 5G-CLARITY: Integrating 5GNR, WiFi and LiFi in Private Networks with Slicing Support
    D. Camps-Mur, M. Ghoraishi, J. Gutierrez, J. Ordonez-Lucena, T. Cogalan, H. Haas, A. Garcia, V. Sark, E. Aumayr S. Meer, S. Yan, A. Mourad, O. Adamuz-Hinojosa, J. Perez-Romero, M. Granda, R. Bian
    2020 European Conference on Networks and Communications (EuCNC), Dubrovnik, Croatia, pp. 1-2, Jun 2020.
    "5G-CLARITY: Integrating 5GNR, WiFi and LiFi in Private Networks with Slicing Support", D. Camps-Mur, M. Ghoraishi, J. Gutierrez, J. Ordonez-Lucena, T. Cogalan, H. Haas, A. Garcia, V. Sark, E. Aumayr S. Meer, S. Yan, A. Mourad, O. Adamuz-Hinojosa, J. Perez-Romero, M. Granda, R. Bian, "2020 European Conference on Networks and Communications (EuCNC), Dubrovnik, Croatia", pp. 1-2, 2020
    close
    This paper introduces 5G-CLARITY, a 5G-PPP project exploring beyond 5G private networks integrating heterogeneous wireless access including 5GNR, WiFi, and LiFi. The project targets enhancements to current 5GNR performance including multi-connectivity and indoor positioning accuracy. It also develops novel management enablers that allow to operate the private network with a high level intent interface, while being able to natively embed Machine Learning (ML) functions.
    close
    @INPROCEEDINGS{Oscar5G-CLARITYEuCNC,
    author={D. {Camps-Mur} and  M. {Ghoraishi} and J. {Gutierrez} and J. {Ordonez-Lucena} and T. {Cogalan} and H. {Haas} and A. {Garcia} and V. {Sark} and E. {Aumayr} S. {Meer} and S. {Yan} and A. {Mourad} and O. {Adamuz-Hinojosa} and J. {Perez-Romero} and M. {Granda} and R. {Bian} },
    booktitle={2020 European Conference on Networks and Communications (EuCNC), Dubrovnik, Croatia},
    title={5G-CLARITY: Integrating 5GNR, WiFi and LiFi in Private Networks with Slicing Support},
    year={2020},
    volume={},
    number={},
    pages={1-2},
    abstract={This paper introduces 5G-CLARITY, a 5G-PPP project exploring beyond 5G private networks integrating heterogeneous wireless access including 5GNR, WiFi, and LiFi. The project targets enhancements to current 5GNR performance including multi-connectivity and indoor positioning accuracy. It also develops novel management enablers that allow to operate the private network with a high level intent interface, while being able to natively embed Machine Learning (ML) functions.},
    keywords={5G; ML; WiFi;; LiFi; private networks; SDN; NFV},
    doi={},
    ISSN={},
    month={Jun},
    project={5gclarity}
    }
    close


White Papers

  1. AI and ML - Enablers for Beyond 5G Networks
    J. Prados-Garzon, L. Chinchilla-Romero, P. Muñoz, J. J. Ramos-Munoz
    "AI and ML - Enablers for Beyond 5G Networks", J. Prados-Garzon, L. Chinchilla-Romero, P. Muñoz, J. J. Ramos-Munoz, 5G PPP, 2021. DOI: 10.5281/zenodo.4299895
    close
    @techreport{5GPPPWP2021,
      author      = "J. {Prados-Garzon} and L. {Chinchilla-Romero} and P. {Muñoz} and J. J. {Ramos-Munoz}",
      title       = "AI and ML - Enablers for Beyond 5G Networks",
      institution = "5G PPP",
      year        = "2021",
      type        = "whitepaper",
      number      = "",
      address     = "",
      month       = "May",
      note        = "",
      annote      = "",
      DOI = {10.5281/zenodo.4299895},
      URL={https://5g-ppp.eu/wp-content/uploads/2021/05/AI-MLforNetworks-v1-0.pdf},
      project = {5gclarity}
    }
    close


Deliverables

  1. Project H2020 5G-CLARITY (Grant No. 871428): Deliverable D3.2. Design Refinements and Initial Evaluation of the Coexistence, Multi-Connectivity, Resource Management and Positioning Frameworks
    T. Cogalan, D. Camps-Mur, A. Garcia, K. Chackravaram, J. Navarro-Ortiz, J.J. Ramos-Munoz, J.M. Lopez-Soler, S. Videv, A. Yeliskaya, H. Alshaer, S. Raju, R. Bian, J. Gutierrez, V. Sark, M. Goodarzi, M. Ghoraishi
    "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D3.2. Design Refinements and Initial Evaluation of the Coexistence, Multi-Connectivity, Resource Management and Positioning Frameworks", T. Cogalan, D. Camps-Mur, A. Garcia, K. Chackravaram, J. Navarro-Ortiz, J.J. Ramos-Munoz, J.M. Lopez-Soler, S. Videv, A. Yeliskaya, H. Alshaer, S. Raju, R. Bian, J. Gutierrez, V. Sark, M. Goodarzi, M. Ghoraishi, 5G-CLARITY, 2021
    close
    @techreport{5GCLARITYD32,
      author      = "T. {Cogalan} and D. {Camps-Mur} and A. {Garcia} and K. {Chackravaram} and J. {Navarro-Ortiz} and J.J. {Ramos-Munoz} and J.M. {Lopez-Soler} and S. {Videv} and A. {Yeliskaya} and H. {Alshaer} and S. {Raju} and R. {Bian} and J. {Gutierrez} and V. {Sark} and M. {Goodarzi} and M. {Ghoraishi}",
      title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D3.2. Design Refinements and Initial Evaluation of the Coexistence, Multi-Connectivity, Resource Management and Positioning Frameworks",
      institution = "5G-CLARITY",
      year        = "2021",
      type        = "deliverable",
      month       = "May",
      URL         = {https://www.5gclarity.com/wp-content/uploads/2021/06/5GC-CLARITY_D32.pdf},
      project     = {5gclarity}
    }
    close

  2. Project H2020 5G-CLARITY (Grant No. 871428): Deliverable D6.3. Mid-term report on disseminations and communications activities
    J. M. Lopez-Soler, T. Cogalan, R. Bian, J. Gutierrez, M. Ghoraishi
    "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D6.3. Mid-term report on disseminations and communications activities", J. M. Lopez-Soler, T. Cogalan, R. Bian, J. Gutierrez, M. Ghoraishi, 5G-CLARITY, 2021
    close
    @techreport{5GCLARITYD63,
      author      = "J. M. {Lopez-Soler} and T. Cogalan and R. Bian and J. Gutierrez and M. Ghoraishi",
      title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D6.3. Mid-term report on disseminations and communications activities",
      institution = "5G-CLARITY",
      year        = "2021",
      type        = "deliverable",
      month       = "May",
      URL         = {https://www.5gclarity.com/wp-content/uploads/2021/05/5G-CLARITY_D63.pdf},
      project     = {5gclarity}
    }
    close

  3. Project H2020 5G-CLARITY (Grant No. 871428): Deliverable D5.1. Specification of use cases and demonstration plan
    M. Ghoraishi, D. Camps-Mur, H. Khalili, V. Sark, J. Gutierrez, T. Cogalan, S. Yan, C. Colman-Meixner, H. Falaki, A. Emami, A. Garcia, J. A. Amoros, M. A. Granda, J. Navarro-Ortiz, J. J. Ramos-Munoz, R. Bian, E. Poves, S. Videv, J. Ordonez-Lucena, M. Ghoraishi
    "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D5.1. Specification of use cases and demonstration plan", M. Ghoraishi, D. Camps-Mur, H. Khalili, V. Sark, J. Gutierrez, T. Cogalan, S. Yan, C. Colman-Meixner, H. Falaki, A. Emami, A. Garcia, J. A. Amoros, M. A. Granda, J. Navarro-Ortiz, J. J. Ramos-Munoz, R. Bian, E. Poves, S. Videv, J. Ordonez-Lucena, M. Ghoraishi, 5G-CLARITY, 2021
    close
    @techreport{5GCLARITYD51,
      author      = "M. Ghoraishi and D. {Camps-Mur} and H. Khalili and V. Sark and J. Gutierrez and T. Cogalan and S. Yan and C. {Colman-Meixner} and H. Falaki and A. Emami and A. Garcia and J. A. Amoros and M. A. Granda and J. {Navarro-Ortiz} and J. J. {Ramos-Munoz} and R. Bian and E. Poves and S. Videv and J. {Ordonez-Lucena} and M. Ghoraishi",
      title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D5.1. Specification of use cases and demonstration plan",
      institution = "5G-CLARITY",
      year        = "2021",
      type        = "deliverable",
      month       = "Feb",
      URL         = {https://www.5gclarity.com/wp-content/uploads/2021/02/5G-CLARITY_D51.pdf},
      project     = {5gclarity}
    }
    close

  4. Project H2020 5G-CLARITY (Grant No. 871428): Deliverable D4.1. Initial design of the SDN/NFV platform and identification of target 5G-CLARITY ML algorithms
    D. Camps-Mur, H. Khalili, E. Aumayr, S. Meer, P. Ameigeiras, J. Prados-Garzon, O. Adamuz-Hinojosa, L. Chinchilla, P. Muñoz, A. Mourad, I. Hemadeh, T. Cogalan, M. Goodarzi, J. Gutierrez, V. Sark, N. Odhah, R. Bian, S. Videv, A. Garcia, C. Colman-Meixner, S. Yan, X. Zou, J. Perez-Romero, O. Sallent, I. Vila, R. Ferrus, J. Ordonez-Lucena, M. Ghoraishi
    "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D4.1. Initial design of the SDN/NFV platform and identification of target 5G-CLARITY ML algorithms", D. Camps-Mur, H. Khalili, E. Aumayr, S. Meer, P. Ameigeiras, J. Prados-Garzon, O. Adamuz-Hinojosa, L. Chinchilla, P. Muñoz, A. Mourad, I. Hemadeh, T. Cogalan, M. Goodarzi, J. Gutierrez, V. Sark, N. Odhah, R. Bian, S. Videv, A. Garcia, C. Colman-Meixner, S. Yan, X. Zou, J. Perez-Romero, O. Sallent, I. Vila, R. Ferrus, J. Ordonez-Lucena, M. Ghoraishi, 5G-CLARITY, 2020
    close
    @techreport{5GCLARITYD41,
      author      = "D. {Camps-Mur} and H. Khalili and E. Aumayr and S. Meer and P. Ameigeiras and J. {Prados-Garzon} and O. {Adamuz-Hinojosa} and L. Chinchilla and P. Muñoz and A. Mourad and I. Hemadeh and T. Cogalan and M. Goodarzi and J. Gutierrez and V. Sark and N. Odhah and R. Bian and S. Videv and A. Garcia and C. {Colman-Meixner} and S. Yan and X. Zou and J. {Perez-Romero} and O. Sallent and I. Vila and R. Ferrus and J. {Ordonez-Lucena} and M. Ghoraishi",
      title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D4.1. Initial design of the {SDN}/{NFV} platform and identification of target {5G-CLARITY} {ML} algorithms",
      institution = "5G-CLARITY",
      year        = "2020",
      type        = "deliverable",
      month       = "Oct",
      URL         = {https://www.5gclarity.com/wp-content/uploads/2020/12/5G-CLARITY_D41.pdf},
      project     = {5gclarity}
    }
    close

  5. Project H2020 5G-CLARITY (Grant No. 871428): Deliverable D2.2. Primary system architecture
    J. Ordonez-Lucena, D. Camps-Mur, H. Khalili, A. Garcia, A. Mourad, I. Hemadeh, J. P. Kainulainen, P. Ameigeiras, J. Prados-Garzon, O. Adamuz-Hinojosa, T. Cogalan, R. Bian, E. Aumayr, S. Meer, C. Colman, S. Yan, H. Frank, A. Emami, J. Gutierrez, V. Sark, M. Ghoraishi
    "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D2.2. Primary system architecture", J. Ordonez-Lucena, D. Camps-Mur, H. Khalili, A. Garcia, A. Mourad, I. Hemadeh, J. P. Kainulainen, P. Ameigeiras, J. Prados-Garzon, O. Adamuz-Hinojosa, T. Cogalan, R. Bian, E. Aumayr, S. Meer, C. Colman, S. Yan, H. Frank, A. Emami, J. Gutierrez, V. Sark, M. Ghoraishi, 5G-CLARITY, 2020
    close
    @techreport{5GCLARITYD22,
      author      = "J. {Ordonez-Lucena} and D. {Camps-Mur} and H. Khalili and A. Garcia and A. Mourad and I. Hemadeh and J. P. Kainulainen and P. Ameigeiras and J. {Prados-Garzon} and O. {Adamuz-Hinojosa} and T. Cogalan and R. Bian and E. Aumayr and S. Meer and C. Colman and S. Yan and H. Frank and A. Emami and J. Gutierrez and V. Sark and M. Ghoraishi",
      title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D2.2. Primary system architecture",
      institution = "5G-CLARITY",
      year        = "2020",
      type        = "deliverable",
      month       = "Oct",
      URL         = {https://www.5gclarity.com/wp-content/uploads/2020/12/5G-CLARITY_D22.pdf},
      project     = {5gclarity}
    }
    close

  6. Project H2020 5G-CLARITY (Grant No. 871428): Deliverable D2.1. Use case specifications and requirements
    M. Granda-Trigo, J. Ordonez-Lucena, D. Camps, A. Garcia, G. Rigazzi, P. Ameigeiras, J. Prados-Garzon, E. Aumayr, T. Cogalan, S. Yan, M. Ghoraishi, J. Gutierrez
    "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D2.1. Use case specifications and requirements", M. Granda-Trigo, J. Ordonez-Lucena, D. Camps, A. Garcia, G. Rigazzi, P. Ameigeiras, J. Prados-Garzon, E. Aumayr, T. Cogalan, S. Yan, M. Ghoraishi, J. Gutierrez, 5G-CLARITY, 2020
    close
    @techreport{5GCLARITYD21,
      author      = "M. Granda-Trigo and J. Ordonez-Lucena and D. Camps and A. Garcia and G. Rigazzi and P. Ameigeiras and J. {Prados-Garzon} and E. Aumayr and T. Cogalan and S. Yan and M. Ghoraishi and J. Gutierrez",
      title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D2.1. Use case specifications and requirements",
      institution = "5G-CLARITY",
      year        = "2020",
      type        = "deliverable",
      month       = "March",
      URL         = {https://www.5gclarity.com/wp-content/uploads/2020/06/5G-CLARITY_D2.1.pdf},
      project     = {5gclarity}
    }
    close

  7. Project H2020 5G-CLARITY (Grant No. 871428): Deliverable D6.1. Plan for explotation and dissemination of the project results
    J. M. Lopez-Soler, O. Adamuz-Hinojosa, J. Navarro-Ortiz, L. Chinchilla-Romero, J. Prados-Garzon, J. Ordonez-Lucena, G. Rigazzi, U. Olvera-Hernandez, D. Camps-Mur, A. Garcia, T. Cogalan, S. Yan, R. Bian, E. Aumayr, M. A. Granda, J. Gutierrez-Teran, M. Ghoraishi
    "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D6.1. Plan for explotation and dissemination of the project results", J. M. Lopez-Soler, O. Adamuz-Hinojosa, J. Navarro-Ortiz, L. Chinchilla-Romero, J. Prados-Garzon, J. Ordonez-Lucena, G. Rigazzi, U. Olvera-Hernandez, D. Camps-Mur, A. Garcia, T. Cogalan, S. Yan, R. Bian, E. Aumayr, M. A. Granda, J. Gutierrez-Teran, M. Ghoraishi, 5G-CLARITY, 2020
    close
    @techreport{5GCLARITYD61,
      author      = "J. M. {Lopez-Soler} and O. {Adamuz-Hinojosa} and J. {Navarro-Ortiz} and L. {Chinchilla-Romero} and J. {Prados-Garzon} and J. {Ordonez-Lucena} and G. {Rigazzi} and U. {Olvera-Hernandez} and D. {Camps-Mur} and A. {Garcia} and T. {Cogalan} and S. {Yan} and R. {Bian} and E. {Aumayr} and M. A. {Granda} and J. {Gutierrez-Teran} and M. Ghoraishi",
      title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D6.1. Plan for explotation and dissemination of the project results",
      institution = "5G-CLARITY",
      year        = "2020",
      type        = "deliverable",
      month       = "Jan",
      URL         = {https://www.5gclarity.com/wp-content/uploads/2020/06/5G-CLARITY_D61.pdf},
      project     = {5gclarity}
    }
    close