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Scopus Author ID: 57211336100

Keywords

5G/6G, MAC layer, RRM, Reinforcement learning, Deep learning, SCMA, NOMA

Countries

Italy

Biography

Luciano Miuccio received the bachelor's degree in Electronics Engineering, and the master's degree in Telecommunications Engineering (cum laude) from the Department of Electrical, Electronics and Computer Engineering, University of Catania, Italy, in 2015 and 2018, respectively. From May 2019 to September 2019, he was an early-stage researcher in "Study of methodologies for the multi-objective optimization of parametric systems" at the University of Catania. In November 2022 he received the Ph.D. in "Systems, Energy, Computer and Telecommunications Engineering" at the University of Catania (with the additional label of “Doctor Europaeus”). He was a Visiting Ph.D. Student with the Centre for Wireless Communications (CWC), Oulu, Finland, for five months, in 2022. He is currently an assistant professor at the University of Catania. His scientific interests include radio resource management, NOMA techniques, green networking, artificial intelligence for B5G/6G radio access networks.

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Education and qualifications (1)

University of Catania: Catania, IT

2019-11-01 to 2022-11-24 | PhD (Department of Electrical, Electronics, and Computer engineering)
Education
Source: Self-asserted source
Luciano Miuccio

Works (17)

On Learning Generalized Wireless MAC Communication Protocols via a Feasible Multi-Agent Reinforcement Learning Framework

IEEE Transactions on Machine Learning in Communications and Networking
2024 | Journal article
DOI: 10.1109/TMLCN.2024.3368367
Contributors: Luciano Miuccio; Salvatore Riolo; Sumudu Samarakoon; Mehdi Bennis; Daniela Panno
Source: check_circle
Crossref

On Learning Intrinsic Rewards for Faster Multi-Agent Reinforcement Learning based MAC Protocol Design in 6G Wireless Networks

arXiv
2023 | Other
DOI: 10.48550/arXiv.2302.14765
EID:

2-s2.0-85150646012

Part of ISSN: 23318422
Contributors: Miuccio, L.; Riolo, S.; Bennis, M.; Panno, D.
Source: Self-asserted source
Luciano Miuccio via Scopus - Elsevier

On Learning Intrinsic Rewards for Faster Multi-Agent Reinforcement Learning based MAC Protocol Design in 6G Wireless Networks

IEEE International Conference on Communications
2023 | Conference paper
DOI: 10.1109/ICC45041.2023.10279625
EID:

2-s2.0-85178277843

ISBN: 9781538674628
Part of ISSN: 15503607
Contributors: Miuccio, L.; Riolo, S.; Bennis, M.; Panno, D.
Source: Self-asserted source
Luciano Miuccio via Scopus - Elsevier

An Energy-Efficient DL-Aided Massive Multiple Access Scheme for IoT Scenarios in Beyond 5G Networks

IEEE Internet of Things Journal
2023-05-01 | Journal article
DOI: 10.1109/JIOT.2022.3231128
Contributors: Luciano Miuccio; Daniela Panno; Salvatore Riolo
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A Flexible Encoding/Decoding Procedure for 6G SCMA Wireless Networks via Adversarial Machine Learning Techniques

IEEE Transactions on Vehicular Technology
2023-03 | Journal article
DOI: 10.1109/TVT.2022.3216028
Contributors: Luciano Miuccio; Daniela Panno; Salvatore Riolo
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Learning Generalized Wireless MAC Communication Protocols via Abstraction

arXiv
2022 | Other
DOI: 10.48550/arXiv.2206.06331
EID:

2-s2.0-85132940219

Part of ISSN: 23318422
Contributors: Miuccio, L.; Riolo, S.; Samarakoon, S.; Panno, D.; Bennis, M.
Source: Self-asserted source
Luciano Miuccio via Scopus - Elsevier

Learning Generalized Wireless MAC Communication Protocols via Abstraction

Proceedings - IEEE Global Communications Conference, GLOBECOM
2022 | Conference paper
DOI: 10.1109/GLOBECOM48099.2022.10000805
EID:

2-s2.0-85146954014

Part of ISSN: 25766813 23340983
Contributors: Miuccio, L.; Riolo, S.; Samarakoon, S.; Panno, D.; Bennis, M.
Source: Self-asserted source
Luciano Miuccio via Scopus - Elsevier

A QoS-aware and channel-aware Radio Resource Management framework for multi-numerology systems

Computer Communications
2022-07 | Journal article
DOI: 10.1016/j.comcom.2022.05.009
Contributors: Luciano Miuccio; Daniela Panno; Pietro Pisacane; Salvatore Riolo
Source: check_circle
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A Wasserstein GAN Autoencoder for SCMA Networks

IEEE Wireless Communications Letters
2022-06 | Journal article
DOI: 10.1109/LWC.2022.3164979
Contributors: Luciano Miuccio; Daniela Panno; Salvatore Riolo
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Channel-Aware and QoS-Aware Downlink Resource Allocation for Multi-numerology Based 5G NR Systems

2021 19th Mediterranean Communication and Computer Networking Conference, MedComNet 2021
2021 | Conference paper
DOI: 10.1109/MEDCOMNET52149.2021.9501268
EID:

2-s2.0-85124698835

ISBN: 9781665435901
Contributors: Miuccio, L.; Panno, D.; Pisacane, P.; Riolo, S.
Source: Self-asserted source
Luciano Miuccio via Scopus - Elsevier

Implementation of a Simulation Environment for Multi-Numerology Scenarios in 5G Vienna Link Level Simulator

2021 IEEE International Conference on Computing, ICOCO 2021
2021 | Conference paper
DOI: 10.1109/ICOCO53166.2021.9673510
EID:

2-s2.0-85125318130

ISBN: 9781665436892
Contributors: Miuccio, L.; Panno, D.; Pollara, P.; Riolo, S.
Source: Self-asserted source
Luciano Miuccio via Scopus - Elsevier

A DNN-based estimate of the PRACH traffic load for massive IoT scenarios in 5G networks and beyond

Computer Networks
2021-12 | Journal article
DOI: 10.1016/j.comnet.2021.108608
Contributors: Luciano Miuccio; Daniela Panno; Salvatore Riolo
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Modeling and Analysis of Tagged Preamble Transmissions in Random Access Procedure for mMTC Scenarios

IEEE Transactions on Wireless Communications
2021-07 | Journal article
DOI: 10.1109/TWC.2021.3057932
Contributors: Salvatore Riolo; Daniela Panno; Luciano Miuccio
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A New Contention-Based PUSCH Resource Allocation in 5G NR for mMTC Scenarios

IEEE Communications Letters
2021-03 | Journal article
DOI: 10.1109/LCOMM.2020.3040504
Contributors: Luciano Miuccio; Daniela Panno; Salvatore Riolo
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Joint Control of Random Access and Dynamic Uplink Resource Dimensioning for Massive MTC in 5G NR Based on SCMA

IEEE Internet of Things Journal
2020-06 | Journal article
DOI: 10.1109/JIOT.2020.2974402
Contributors: Luciano Miuccio; Daniela Panno; Salvatore Riolo
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Dynamic uplink resource dimensioning for massive MTC in 5G networks based on SCMA

European Wireless 2019 Conference, EW 2019
2019 | Conference paper
EID:

2-s2.0-85073513962

ISBN: 9783800749492
Contributors: Miuccio, L.; Panno, D.; Riolo, S.
Source: Self-asserted source
Luciano Miuccio via Scopus - Elsevier

Joint congestion control and resource allocation for massive MTC in 5G networks based on SCMA

ConTEL 2019 - 15th International Conference on Telecommunications, Proceedings
2019 | Conference paper
DOI: 10.1109/ConTEL.2019.8848540
EID:

2-s2.0-85073536138

ISBN: 9781728120911
Contributors: Miuccio, L.; Panno, D.; Riolo, S.
Source: Self-asserted source
Luciano Miuccio via Scopus - Elsevier
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