"Computationally Efficient UE Blocking Probability Model for GBR Services in Beyond 5G RAN", Oscar Adamuz-Hinojosa, Pablo Ameigeiras, Pablo Muñoz, Juan M. Lopez-Soler, IEEE Access, pp. 1-1, 2024. DOI: 10.1109/ACCESS.2024.3377112

@ARTICLE{10471531,
  author={Adamuz-Hinojosa, Oscar and Ameigeiras, Pablo and Muñoz, Pablo and Lopez-Soler, Juan M.},
  journal={IEEE Access}, 
  title={Computationally Efficient UE Blocking Probability Model for GBR Services in Beyond 5G RAN}, 
  year={2024},
  volume={},
  number={},
  pages={1-1},
  keywords={Signal to noise ratio;Computational modeling;Interference;Data models;Probability;Planning;Mathematical models;Beyond 5G;Blocking probability;GBR service;Markov Chain;Proportional Fair;Round Robin},
  doi={10.1109/ACCESS.2024.3377112},
  impact = {(IF=3.9, Q2)},
  project = {6gchronos|6ginspire}}

"Load balancing and handover joint optimization in LTE networks using Fuzzy Logic and Reinforcement Learning", P. Munoz, R. Barco, I. de la Bandera, Computer Networks, 76, pp. 112-125, 2015. DOI: https://doi.org/10.1016/j.comnet.2014.10.027

With the growing deployment of cellular networks, operators have to devote significant manual effort to network management. As a result, Self-Organizing Networks (SONs) have become increasingly important in order to raise the level of automated operation in cellular technologies. In this context, Load Balancing (LB) and Handover Optimization (HOO) have been identified by industry as key self-organizing mechanisms for the Radio Access Networks (RANs). However, most efforts have been focused on developing a stand-alone entity for each self-organizing mechanism, which will run in parallel with other entities, as well as designing coordination mechanisms in charge of stabilizing the network as a whole. Due to the importance of LB and HOO, in this paper, a unified self-management mechanism based on Fuzzy Logic and Reinforcement Learning is proposed. In particular, the proposed algorithm modifies handover parameters to optimize the main Key Performance Indicators related to LB and HOO. Results show that the proposed scheme effectively provides better performance than independent entities running simultaneously in the network.

@article{MUNOZ2015112,
title = {Load balancing and handover joint optimization in LTE networks using Fuzzy Logic and Reinforcement Learning},
journal = {Computer Networks},
volume = {76},
pages = {112-125},
year = {2015},
issn = {1389-1286},
doi = {https://doi.org/10.1016/j.comnet.2014.10.027},
url = {https://www.sciencedirect.com/science/article/pii/S1389128614003892},
author = {P. Munoz and R. Barco and I. {de la Bandera}},
keywords = {Load balancing, Handover, Self-organizing networks, Long-term evolution, Fuzzy logic, Reinforcement learning},
abstract = {With the growing deployment of cellular networks, operators have to devote significant manual effort to network management. As a result, Self-Organizing Networks (SONs) have become increasingly important in order to raise the level of automated operation in cellular technologies. In this context, Load Balancing (LB) and Handover Optimization (HOO) have been identified by industry as key self-organizing mechanisms for the Radio Access Networks (RANs). However, most efforts have been focused on developing a stand-alone entity for each self-organizing mechanism, which will run in parallel with other entities, as well as designing coordination mechanisms in charge of stabilizing the network as a whole. Due to the importance of LB and HOO, in this paper, a unified self-management mechanism based on Fuzzy Logic and Reinforcement Learning is proposed. In particular, the proposed algorithm modifies handover parameters to optimize the main Key Performance Indicators related to LB and HOO. Results show that the proposed scheme effectively provides better performance than independent entities running simultaneously in the network.},
impact ={(IF=1.44, Q2)}
}

"Dynamic traffic steering based on fuzzy Q-Learning approach in a multi-RAT multi-layer wireless network", P. Munoz, D. Laselva, R. Barco, P. Mogensen, Computer Networks, 71, pp. 100-116, 2014. DOI: https://doi.org/10.1016/j.comnet.2014.06.003

The infrastructure of current cellular networks must evolve to cope with the increasing demand for mobile-broadband services. Heterogeneous networks are an attractive solution for operators to expand network capacity, based on deploying different Radio Access Technologies, cell sizes and carrier frequencies in the same environment. As a result, operators gain flexibility to distribute traffic across the different networks (or layers) in order to make a more efficient use of resources and enhance network performance. In this work, a dynamic traffic steering technique in multi-RAT multi-layer wireless networks is proposed. In particular, a fuzzy rule-based reinforcement learning algorithm modifies handover parameters according to a specific policy set by the operator, which typically searches for a trade-off between key performance indicators. Results show that the proposed optimization algorithm provides good flexibility to support different policies by simply adjusting some weighting factors. In addition, the Q-Learning algorithm is shown as an effective solution to adapt the network to context variations, such as those produced in the user spatial distribution.

@article{MUNOZ2014100,
title = {Dynamic traffic steering based on fuzzy Q-Learning approach in a multi-RAT multi-layer wireless network},
journal = {Computer Networks},
volume = {71},
pages = {100-116},
year = {2014},
issn = {1389-1286},
doi = {https://doi.org/10.1016/j.comnet.2014.06.003},
url = {https://www.sciencedirect.com/science/article/pii/S1389128614002266},
author = {P. Munoz and D. Laselva and R. Barco and P. Mogensen},
keywords = {Traffic steering, Q-Learning, Fuzzy logic controller, Handover, Heterogeneous networks},
abstract = {The infrastructure of current cellular networks must evolve to cope with the increasing demand for mobile-broadband services. Heterogeneous networks are an attractive solution for operators to expand network capacity, based on deploying different Radio Access Technologies, cell sizes and carrier frequencies in the same environment. As a result, operators gain flexibility to distribute traffic across the different networks (or layers) in order to make a more efficient use of resources and enhance network performance. In this work, a dynamic traffic steering technique in multi-RAT multi-layer wireless networks is proposed. In particular, a fuzzy rule-based reinforcement learning algorithm modifies handover parameters according to a specific policy set by the operator, which typically searches for a trade-off between key performance indicators. Results show that the proposed optimization algorithm provides good flexibility to support different policies by simply adjusting some weighting factors. In addition, the Q-Learning algorithm is shown as an effective solution to adapt the network to context variations, such as those produced in the user spatial distribution.},
impact = {(IF=1.25, Q2)}
}

"Optimization of load balancing using fuzzy Q-Learning for next generation wireless networks", P. Munoz, R. Barco, I. de la Bandera, Expert Systems with Applications, 40 (4), pp. 984-994, 2013. DOI: https://doi.org/10.1016/j.eswa.2012.08.071

Load balancing is considered by the 3GPP as an important issue in Self-Organizing Networks due to its effectiveness to increase network capacity. In next generation wireless networks, load balancing can be easily implemented by tuning handover (HO) margins, achieving a decrease in call blocking. However, call dropping can be increased as a negative effect of the HO-based load balancing, because users usually are handed over to cells where the radio conditions are worse. In this work, a Fuzzy Logic Controller (FLC) optimized by the fuzzy Q-Learning algorithm is proposed for the load balancing problem, with the aim of decreasing call blocking in congested cells, while at the same time restricting call dropping in neighboring cells according to the network policy. In particular, two different approaches for the FLC optimization are evaluated in this work, highlighting that one of the proposed methods allows to accurately preserve the call quality constraint during the load balancing, while the other can adapt to network variations. Results show that the optimized FLC provides a notable reduction in call blocking while preserving call dropping under the operator constraint.

@article{MUNOZ2013984,
title = {Optimization of load balancing using fuzzy Q-Learning for next generation wireless networks},
journal = {Expert Systems with Applications},
volume = {40},
number = {4},
pages = {984-994},
year = {2013},
issn = {0957-4174},
doi = {https://doi.org/10.1016/j.eswa.2012.08.071},
url = {https://www.sciencedirect.com/science/article/pii/S0957417412010445},
author = {P. Munoz and R. Barco and I. {de la Bandera}},
keywords = {Fuzzy Q-Learning, Fuzzy Logic Controller, Handover, Load balancing},
abstract = {Load balancing is considered by the 3GPP as an important issue in Self-Organizing Networks due to its effectiveness to increase network capacity. In next generation wireless networks, load balancing can be easily implemented by tuning handover (HO) margins, achieving a decrease in call blocking. However, call dropping can be increased as a negative effect of the HO-based load balancing, because users usually are handed over to cells where the radio conditions are worse. In this work, a Fuzzy Logic Controller (FLC) optimized by the fuzzy Q-Learning algorithm is proposed for the load balancing problem, with the aim of decreasing call blocking in congested cells, while at the same time restricting call dropping in neighboring cells according to the network policy. In particular, two different approaches for the FLC optimization are evaluated in this work, highlighting that one of the proposed methods allows to accurately preserve the call quality constraint during the load balancing, while the other can adapt to network variations. Results show that the optimized FLC provides a notable reduction in call blocking while preserving call dropping under the operator constraint.},
impact = {(IF=1.96, Q1)}
}

"Design of a Computationally Efficient Dynamic System-Level Simulator for Enterprise LTE Femtocell Scenarios", J. M. Ruiz-Aviles, S. Luna-Ramirez, M. Toril, F. Ruiz, I. de la Bandera, P. Munoz, R. Barco, P. Lazaro, V. Buenestado, Journal of Electrical and Computer Engineering, 2012, pp. 14, 2012. DOI: https://doi.org/10.1155/2012/802606

In the context of Long-Term Evolution (LTE), the next generation mobile telecommunication network, femtocells are low-power base stations that efficiently provide coverage and capacity indoors. This paper presents a computationally efficient dynamic system-level LTE simulator for enterprise femtocell scenarios. The simulator includes specific mobility and traffic and propagation models for indoor environments. A physical layer abstraction is performed to predict link-layer performance with low computational cost. At link layer, two important functions are included to increase network capacity: Link Adaptation and Dynamic Scheduling. At network layer, other Radio Resource Management functionalities, such as Admission Control and Mobility Management, are also included. The resulting tool can be used to test and validate optimization algorithms in the context of Self-Organizing Networks (SON).

@article{PMunoz2012,
title = {Design of a Computationally Efficient Dynamic System-Level Simulator for Enterprise LTE Femtocell Scenarios},
journal = {Journal of Electrical and Computer Engineering},
author = {J. M. Ruiz-Aviles and S. Luna-Ramirez and M. Toril and F. Ruiz and I. de la Bandera and P. Munoz and R. Barco and P. Lazaro and V. Buenestado},
volume = {2012},
pages = {14},
year = {2012},
issn = {1018-4864},
doi = {https://doi.org/10.1155/2012/802606},
url = {https://www.hindawi.com/journals/jece/2012/802606/},
abstract = {In the context of Long-Term Evolution (LTE), the next generation mobile telecommunication network, femtocells are low-power base stations that efficiently provide coverage and capacity indoors. This paper presents a computationally efficient dynamic system-level LTE simulator for enterprise femtocell scenarios. The simulator includes specific mobility and traffic and propagation models for indoor environments. A physical layer abstraction is performed to predict link-layer performance with low computational cost. At link layer, two important functions are included to increase network capacity: Link Adaptation and Dynamic Scheduling. At network layer, other Radio Resource Management functionalities, such as Admission Control and Mobility Management, are also included. The resulting tool can be used to test and validate optimization algorithms in the context of Self-Organizing Networks (SON).}
}

"Flow Prioritization for TSN Asynchronous Traffic Shapers", Julia Caleya-Sanchez, Jonathan Prados-Garzon, Lorena Chinchilla-Romero, Pablo Munoz-Luengo, Pablo Ameigeiras, "International Federation for Information Processing (IFIP) Networking 2023 - TENSOR workshop", 2023

@INPROCEEDINGS{EUCNC2023,
   author       = {Caleya-Sanchez, Julia and Prados-Garzon, Jonathan and Chinchilla-Romero, Lorena and Munoz-Luengo, Pablo and Ameigeiras, Pablo},
   title        = {Flow Prioritization for TSN Asynchronous Traffic Shapers},
   booktitle    = {International Federation for Information Processing (IFIP) Networking 2023 - TENSOR workshop},
   year         = {2023},
   publisher    = {IFIP Technical Committee on Communication Systems (TC6)},
   month        = {June},
   address      = {Barcelona, Spain},
   COMMENTdoi   = {xxx},
   project      = {5gclarity|true5g|6gchronos},
   COMMENTurl   = {https://doi.org/xxx}
}

"Autonomous Radio Resource Provisioning in Multi-WAT Private 5G RANs based on DRL", L. Chinchilla-Romero, J. Prados-Garzon, P. Munoz, P. Ameigeiras, J. J. Ramos-Munoz, "IEEE Wireless Communications and Networking Conference (WCNC), Glasgow", 2023

@INPROCEEDINGS{AutoCh23,
  author       = {L. Chinchilla-Romero and J. Prados-Garzon and P. Munoz and P. Ameigeiras and J. J. Ramos-Munoz},
  booktitle    = {IEEE Wireless Communications and Networking Conference (WCNC), Glasgow},
  title        = {Autonomous Radio Resource Provisioning in Multi-WAT Private 5G RANs based on DRL},
  year         = {2023},
  publisher    = {IEEE},
  month        = {Mar},
  address      = {Glasgow, Scotland, UK},
  COMMENTdoi   = {xxx},
  project      = {5gclarity|true5g|6gchronos},
  COMMENTurl   = {https://doi.org/xxx}}

"URLLC Achieved Data Rate through Exploiting Multi-Connectivity in Industrial Private 5G Networks with Multi-WAT RANs", L. Chinchilla-Romero, J. Prados-Garzon, P. Munoz, P. Ameigeiras, J. M. Lopez-Soler, "IEEE Wireless Communications and Networking Conference (WCNC), Glasgow", 2023

@INPROCEEDINGS{URLLC_Ch23,
  author       = {L. Chinchilla-Romero and J. Prados-Garzon and P. Munoz and P. Ameigeiras and J. M. Lopez-Soler},
  booktitle    = {IEEE Wireless Communications and Networking Conference (WCNC), Glasgow},
  title        = {URLLC Achieved Data Rate through Exploiting Multi-Connectivity in Industrial Private 5G Networks with Multi-WAT RANs},
  year         = {2023},
  publisher    = {IEEE},
  month        = {Mar},
  address      = {Glasgow, Scotland, UK},
  COMMENTdoi   = {xxx},
  project      = {5gclarity|true5g|6gchronos},
  COMMENTurl   = {https://doi.org/xxx}}

"WIMUNET: Current research on Internet of (Robotic) things and 5G", P. Munoz, L. Chinchilla-Romero, N. Chinchilla-Romero, J. Prados-Garzon, O. Adamuz-Hinojosa, F. Delgado-Ferro, J. Caleya-Sanchez, P. Rodriguez-Martin, P. Ameigeiras, J. Navarro-Ortiz, J. J. Ramos-Munoz, J. M. Lopez-Soler, "Arqus Research Focus Forum - Artificial Intelligence and its applications, Granada", 2022

@INPROCEEDINGS{Auto_Ch23,
  author={P. Munoz and L. Chinchilla-Romero and N. Chinchilla-Romero and J. Prados-Garzon and O. Adamuz-Hinojosa and F. Delgado-Ferro and J. Caleya-Sanchez and P. Rodriguez-Martin and P. Ameigeiras and J. Navarro-Ortiz and J. J. Ramos-Munoz and J. M. Lopez-Soler},
  booktitle={Arqus Research Focus Forum - Artificial Intelligence and its applications, Granada},
  title={WIMUNET: Current research on Internet of (Robotic) things and 5G},
  year={2022},
  volume={},
  number={},
  pages={},
  project      = {5gclarity|true5g|6gchronos|premonition},
  doi={}}

"DRL-assisted Radio Resource Provisioning in multi-WAT Private 5G Networks", L. Chinchilla-Romero, J. Prados-Garzon, P. Munoz, P. Ameigeiras, J. J. Ramos-Munoz, "XXXVII Simposio de la URSI (Union Cientifica Internacional de Radio), Malaga", 2022

@INPROCEEDINGS{DRL_Ch22,
  author={L. Chinchilla-Romero and J. Prados-Garzon and P. Munoz and P. Ameigeiras and J. J. Ramos-Munoz},
  booktitle={XXXVII Simposio de la URSI (Union Cientifica Internacional de Radio), Malaga},
  title={DRL-assisted Radio Resource Provisioning in multi-WAT Private 5G Networks},
  year={2022},
  volume={},
  number={},
  pages={},
  project      = {5gclarity|true5g|6gchronos},
  doi={}}

"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

@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}}

"Rendimiento de Redes 4G/5G usando una estacion 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 Ingenieria Telematica (JITEL 2021)", 2021

@INPROCEEDINGS{fdelgado_jitel21a,  author={F. {Delgado-Ferro} and J. {Navarro-Ortiz} and L. {Chinchilla-Romero} and P. {Munoz-Luengo}},  booktitle={XV Jornadas de Ingenieria Telematica (JITEL 2021)}, title={Rendimiento de Redes 4G/5G usando una estacion 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}}

"Improving hardware security for LoRaWAN", J. Navarro-Ortiz, N. Chinchilla-Romero, J. J. Ramos-Munoz, P. Munoz-Luengo, "2019 IEEE Conference on Standards for Communications and Networking (CSCN)", pp. 1-6, 2019. DOI: 10.1109/CSCN.2019.8931397

@Inproceedings{8931397,  author={J. {Navarro-Ortiz} and N. {Chinchilla-Romero} and J. J. {Ramos-Munoz} and P. {Munoz-Luengo}},  booktitle={2019 IEEE Conference on Standards for Communications and Networking (CSCN)},   title={Improving hardware security for LoRaWAN},   year={2019},  volume={},  number={},  pages={1-6},  doi={10.1109/CSCN.2019.8931397}, project="5gcity"}

"WiMuNet's research on 5G and QoE", J. Prados-Garzon, P. Andres-Maldonado, P. Romero-Diaz, J. Navarro-Ortiz, J. J. Ramos-Munoz, P. Ameigeiras, P. Munoz-Luengo, S. Sendra, J. M. Lopez-Soler, "IV Workshop on QoE, QoS on Multimedia Communications (QQCM'18)", 2018

@Inproceedings{jpradosqqcm18,  author={J. {Prados-Garzon} and P. {Andres-Maldonado} and P. {Romero-Diaz} and J. {Navarro-Ortiz} and J. J. {Ramos-Munoz} and P. {Ameigeiras} and P. {Munoz-Luengo} and S. {Sendra} and J. M. {Lopez-Soler}},  booktitle={IV Workshop on QoE, QoS on Multimedia Communications (QQCM'18)}, title={WiMuNet's research on 5G and QoE}, year={2018}, project={5gcity}}

"Wireless and Multimedia Networking laboratory", J. Prados-Garzon, P. Andres-Maldonado, P. Romero-Diaz, J. Navarro-Ortiz, J. J. Ramos-Munoz, P. Ameigeiras, P. Munoz-Luengo, S. Sendra, J. M. Lopez-Soler, "II Workshop on QoE, QoS on Multimedia Communications (QQCM'16)", 2016

@Inproceedings{jpradosqqcm16,  author={J. {Prados-Garzon} and P. {Andres-Maldonado} and P. {Romero-Diaz} and J. {Navarro-Ortiz} and J. J. {Ramos-Munoz} and P. {Ameigeiras} and P. {Munoz-Luengo} and S. {Sendra} and J. M. {Lopez-Soler}},  booktitle={II Workshop on QoE, QoS on Multimedia Communications (QQCM'16)}, title={Wireless and Multimedia Networking laboratory},   year={2016}}

"Analysis of load sharing techniques in enterprise LTE femtocells", J. M. R. Aviles, S. Luna-Ramirez, M. Toril, F. Ruiz, I. de la Bandera-Cascales, P. Munoz-Luengo, "2011 Wireless Advanced", ISBN 978-1457701108, pp. 195-200, 2011. DOI: 10.1109/WiAd.2011.5983310

In cellular networks, traffic demand is unevenly distributed both in time and space. This paper investigates the problem of re-distributing traffic demand between LTE femtocells in an enterprise scenario. A performance comparison of several traffic sharing techniques is carried out based on simulations. For this purpose, an efficient dynamic system-level LTE simulator is built. Results show that the combination of directed retry and load sharing by tuning handover margins and transmit power is an effective means to solve localized congestion problems.

@INPROCEEDINGS{5983310,
	author={J. M. R. {Aviles} and S. {Luna-Ramirez} and M. {Toril} and F. {Ruiz} and I. {de la Bandera-Cascales} and P. {Munoz-Luengo}},
	booktitle={2011 Wireless Advanced},
	title={Analysis of load sharing techniques in enterprise LTE femtocells},
	year={2011},
	volume={},
	number={},
	pages={195-200},
	abstract={In cellular networks, traffic demand is unevenly distributed both in time and space. This paper investigates the problem of re-distributing traffic demand between LTE femtocells in an enterprise scenario. A performance comparison of several traffic sharing techniques is carried out based on simulations. For this purpose, an efficient dynamic system-level LTE simulator is built. Results show that the combination of directed retry and load sharing by tuning handover margins and transmit power is an effective means to solve localized congestion problems.},
	keywords={cellular radio;femtocellular radio;Long Term Evolution;telephone traffic;load sharing techniques analysis;enterprise LTE Femtocells;cellular networks;traffic demand;redistributing traffic demand;traffic sharing techniques;system-level LTE simulator;Femtocells;Computational modeling;Load management;Optimization;Fading;Tuning;Macrocell networks;Mobile network;traffic;load balancing;optimization;handover margins},
	doi={10.1109/WiAd.2011.5983310},
	ISSN={},
	isbn={978-1457701108},
	month={June},
}

"Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D4.3. Evaluation of E2E 5G Infrastructure and Service Slices, and of the Developed Self-Learning ML Algorithms ", J. McNamara, A. Yesilkaya, A. Purwita, C. Colman-Meixner, H. Li, H. Frank, S. Yan, X. Zhou, D. Camps-Mur, D. Gonzalez-Sanchez, I. Soto-Campos, D. Fernandez-Cambronero, J. Prados-Garzon, J. J. Ramos-Munoz, L. Chinchilla-Romero, P. Munoz-Luengo, J. Perez-Romero, O. Sallent, I. Vila, J. A. Ordonez-Lucena, I Dominguez-Martinez, M. Goodarzi, T. Cogalan, M. Ghoraishi, 5G-CLARITY, 2022

@techreport{5GCLARITYD43,
  author      = "J. McNamara and A. Yesilkaya and A. Purwita and C. Colman-Meixner and H. Li and H. Frank and S. Yan and X. Zhou and D. Camps-Mur and D. Gonzalez-Sanchez and I. Soto-Campos and D. Fernandez-Cambronero and J. Prados-Garzon and J. J. Ramos-Munoz and L. Chinchilla-Romero and P. Munoz-Luengo and J. Perez-Romero and O. Sallent and I. Vila and J. A. Ordonez-Lucena and I Dominguez-Martinez and M. Goodarzi and T. Cogalan and M. Ghoraishi",
  title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D4.3. Evaluation of E2E 5G Infrastructure and Service Slices, and of the Developed Self-Learning ML Algorithms ",
  institution = "5G-CLARITY",
  year        = "2022",
  type        = "deliverable",
  month       = "October",
  URL         = {https://5gclarity.com/wp-content/uploads/2023/03/5G-CLARITY-D43-Amended.pdf},
  project     = {5gclarity}
}

"Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D2.4. Final System Architecture and Its Evaluation", A. Tzanakaki, M. Anastasopoulos, J. A. Ordonez-Lucena, D. Camps-Mur, A. Manolopoulos, V. M. Alevizaki, P. Georgiadis, C. Colman-Meixner, S. Yang, H. Alshaer, A. Garcia, K. Chackravaram, J. Prados-Garzon, L. Chinchilla-Romero, P. Ameigeiras, P. Munoz-Luengo, D. Gonzalez-Sanchez, I. Dominguez-Martinez, R. Bian, T. Cogalan, J. McNamara, N. C. Manjappa, R. Vasist, M. Goodarzi, J. Gutierrez, V. Sark, M. Ghoraishi, A. Jain, 5G-CLARITY, 2022

@techreport{5GCLARITYD24,
  author      = "A. Tzanakaki and M. Anastasopoulos and J. A. Ordonez-Lucena and D. Camps-Mur and A. Manolopoulos and V. M. Alevizaki and P. Georgiadis and C. Colman-Meixner and S. Yang and 
  H. Alshaer and A. Garcia and K. Chackravaram and J. Prados-Garzon and L. Chinchilla-Romero and P. Ameigeiras and P. Munoz-Luengo 
  and D. Gonzalez-Sanchez and I. Dominguez-Martinez and R. Bian and T. Cogalan and J. McNamara and N. C. Manjappa and R. Vasist and M. Goodarzi and J. Gutierrez and V. Sark and M. Ghoraishi and A. Jain",
  title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D2.4. Final System Architecture and Its Evaluation",
  institution = "5G-CLARITY",
  year        = "2022",
  type        = "deliverable",
  month       = "October",
  URL         = {https://5gclarity.com/wp-content/uploads/2023/03/5G-CLARITY-D24-Amended.pdf},
  project     = {5gclarity}
}

"Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D6.7. Restricted Deliverable on Exploitation Plan", R. Bian, H. Garcia-Nieto, J. Gutierrez, V. Sark, T. Cogalan, C. Colman-Meixner, A. Garcia, J. A. Amoros, A. Yesilkaya, H. Alshaer, P. Munoz-Luengo, J. M. Lopez-Soler, J. A. Ordonez-Lucena, J. McNamara, M. Ghoraishi, 5G-CLARITY, 2022

@techreport{5GCLARITYD67,
  author      = "R. Bian and H. Garcia-Nieto and J. Gutierrez and V. Sark and T. Cogalan and C. Colman-Meixner and A. Garcia and J. A. Amoros and A. Yesilkaya and H. Alshaer and P. Munoz-Luengo and J. M. Lopez-Soler and J. A. Ordonez-Lucena and J. McNamara and M. Ghoraishi",
  title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D6.7. Restricted Deliverable on Exploitation Plan",
  institution = "5G-CLARITY",
  year        = "2022",
  type        = "deliverable",
  month       = "February",
  URL         = {https://5gclarity.com/wp-content/uploads/2022/07/5G-CLARITY_D67.pdf},
  project     = {5gclarity}
}

"Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D2.3. Primary System Architecture Evaluation", A. Tzanakaki, J. A. Ordonez-Lucena, D. Camps-Mur, A. Manolopoulos, P. Georgiades, V. M. Alevizaki, S. Maglaris, M. Anastasopoulos, A. Tzanakaki, A. Garcia, K. Chackravaram, J. Prados-Garzon, L. Chinchilla-Romero, P. Ameigeiras, P. Munoz-Luengo, H. Alshaer, A. Yesilkaya, R. Bian, T. Cogalan, R. Vasist, M. Goodarzi, J. Gutierrez, V. Sark, M. Ghoraishi, 5G-CLARITY, 2021

@techreport{5GCLARITYD23,
  author      = "A. Tzanakaki and J. A. Ordonez-Lucena and D. Camps-Mur and A. Manolopoulos and P. Georgiades and V. M. Alevizaki and S. Maglaris and M. Anastasopoulos and A. Tzanakaki and A. Garcia and K. Chackravaram and J. Prados-Garzon and L. Chinchilla-Romero and P. Ameigeiras and P. Munoz-Luengo and H. Alshaer and A. Yesilkaya and R. Bian and T. Cogalan and R. Vasist and M. Goodarzi and J. Gutierrez and V. Sark and M. Ghoraishi",
  title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D2.3. Primary System Architecture Evaluation",
  institution = "5G-CLARITY",
  year        = "2021",
  type        = "deliverable",
  month       = "July",
  URL         = {https://5gclarity.com/wp-content/uploads/2021/10/5G-CLARITY_D23.pdf},
  project     = {5gclarity}
}

"Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D4.2. Validation of 5G-CLARITY SDN/NFV Platform, Interface Design with 5G Service Platform, and Initial Evaluation of ML Algorithms", J. Ordonez-Lucena, O. Adamuz-Hinojosa, P. Ameigeiras, L. Chinchilla-Romero, P. Munoz-Luengo, J. Navarro-Ortiz, J. Prados-Garzon, J. J. Ramos-Munoz, D. Camps-Mur, F. Canellas, J. Perez-Romero, O. Sallent, I. Vila, A. Purwita, A. Yesilkaya, A. Garcia, K. Chackravaram, E. Aumayr, J. Mcnamara, C. Colman-Meixner, X. Zhou, A. Emami, S. Yan, S. Raju, R. Bian, T. Cogalan, I. Hemadeh, M. Ghoraishi, 5G-CLARITY, 2021

@techreport{5GCLARITYD42,
  author      = "J. Ordonez-Lucena and O. Adamuz-Hinojosa and P. Ameigeiras and L. Chinchilla-Romero and P. Munoz-Luengo and J. Navarro-Ortiz and J. Prados-Garzon and J. J. Ramos-Munoz and D. Camps-Mur and F. Canellas and J. Perez-Romero and O. Sallent and I. Vila and A. Purwita and A. Yesilkaya and A. Garcia and K. Chackravaram and E. Aumayr and J. Mcnamara and C. Colman-Meixner and X. Zhou and A. Emami and S. Yan and S. Raju and R. Bian and T. Cogalan and I. Hemadeh and M. Ghoraishi",
  title       = "Project H2020 5G-CLARITY  (Grant No. 871428): Deliverable D4.2. Validation of 5G-CLARITY SDN/NFV Platform, Interface Design with 5G Service Platform, and Initial Evaluation of ML Algorithms",
  institution = "5G-CLARITY",
  year        = "2021",
  type        = "deliverable",
  month       = "July",
  URL         = {https://5gclarity.com/wp-content/uploads/2021/11/5G-CLARITY_D42.pdf},
  project     = {5gclarity}
}

"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. Munoz, 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

@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. Munoz 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       = "October",
  URL         = {https://www.5gclarity.com/wp-content/uploads/2020/12/5G-CLARITY_D41.pdf},
  project     = {5gclarity}
}

"Metodos de configuracion de redes sensibles al retardo basadas en planificadores con conformacion de trafico asincrono, y con calidad de servicio determinista", Universidad de Granada, Julia Caleya-Sanchez, Jonathan Prados-Garzon, Pablo Ameigeiras, Lorena Chinchilla-Romero, Pablo Munoz-Luengo, Juan M. Lopez-Soler, 2023

@patent{Caleya2023,
	title = {Metodos de configuracion de redes sensibles al retardo basadas en planificadores con conformacion de trafico asincrono, y con calidad de servicio determinista},
	commenturl = {https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2003049354},
	language = {es},
	assignee = {Universidad de Granada},
	commenturldate = {2023-xx-xx},
	author = {Caleya-Sanchez, Julia and Prados-Garzon, Jonathan and Ameigeiras, Pablo and Chinchilla-Romero, Lorena and Munoz-Luengo, Pablo and Lopez-Soler, Juan M.},
	commentmonth = Jun,
	year = {2023},
  project = {6gchronos|true5g|5gclarity}
}