Integrating wireless communication engineering and machine learning

Projektinformationen

WINDMILL

ID Finanzhilfevereinbarung: 813999

DOI

10.3030/813999

Projekt abgeschlossen

EK-Unterschriftsdatum 13 September 2018

Startdatum 1 Januar 2019

Enddatum 30 Juni 2023

Finanziert unter

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Gesamtkosten

€ 4 072 823,64

EU-Beitrag

€ 4 072 823,64

Koordiniert durch

AALBORG UNIVERSITET
Denmark

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

Documents, reports (19)

Final report on prediction and anticipatory optimisation for wireless channels
Novel ML techniques for wireless network optimisation
Report on dissemination/outreach of the project and plan for final two years
Dissemination plan
Supervisory Board of the network

Supervisory Board of the network – due date month 2

Final report on training activities
Initial report on training activities
Intermediate report on training activities
Final report on dissemination/outreach of the project

Final report on disseminationoutreach of the project

Intermediate report on machine learning techniques for wireless channels
Identify challenges of conventional ML in wireless networks
System-wide cognitive optimisation schemes. Final results: cognitive network slicing and related security aspects

Systemwide cognitive optimisation schemes Final results cognitive network slicing and related security aspects

Hierarchical and distributed learning architecture & multi-objective optimisation strategies

Hierarchical and distributed learning architecture multiobjective optimisation strategies

Initial report on MLfor radio resource management and initial datasets
State of the art on context acquisition & anticipatory optimisation techniques for network optimisation
Final report on machine learning techniques for radio resource management
Performance assessment of the proposed ML techniques
Massive-MIMO mmWave channel model and system simulator description
Intermediate report on machine learning techniques for radio resource management

Veröffentlichungen

Conference proceedings (7)

Wireless Control of Autonomous Guided Vehicle Using Reinforcement Learning

Autoren: Pedro M. de Sant Ana, Nikolaj Marchenko, Petar Popovski, Beatriz Soret
Veröffentlicht in: GLOBECOM 2020 - 2020 IEEE Global Communications Conference, 2020, Seite(n) 1-7, ISBN 978-1-7281-8298-8
Herausgeber: IEEE
DOI: 10.1109/globecom42002.2020.9322156

Motion Pattern Recognition in 4D Point Clouds

Autoren: Dariush Salami, Sameera Palipana, Manila Kodali, Stephan Sigg
Veröffentlicht in: 2020 IEEE 30th International Workshop on Machine Learning for Signal Processing (MLSP), 2020, Seite(n) 1-6, ISBN 978-1-7281-6662-9
Herausgeber: IEEE
DOI: 10.1109/mlsp49062.2020.9231569

Coordinated Uplink Precoding for Spatially Consistent mmWave Channel Covariance Measurements

Autoren: Hanan Al-Tous, Parham Kazemi, Olav Tirkkonen
Veröffentlicht in: 2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2020, Seite(n) 1-5, ISBN 978-1-7281-5478-7
Herausgeber: IEEE
DOI: 10.1109/spawc48557.2020.9154333

The challenges of Scheduling and Resource Allocation in IEEE 802.11ad/ay

Autoren: Salman Mohebi, Mattia Lecci, Andrea Zanella, Michele Zorzi
Veröffentlicht in: 2020 Mediterranean Communication and Computer Networking Conference (MedComNet), 2020, Seite(n) 1-4, ISBN 978-1-7281-6248-5
Herausgeber: IEEE
DOI: 10.1109/medcomnet49392.2020.9191491

Team Deep Mixture of Experts for Distributed Power Control

Autoren: Matteo Zecchin, David Gesbert, Marios Kountouris
Veröffentlicht in: 2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2020, Seite(n) 1-5, ISBN 978-1-7281-5478-7
Herausgeber: IEEE
DOI: 10.1109/spawc48557.2020.9154235

Extending the ns-3 QUIC Module

Autoren: Umberto Paro, Federico Chiariotti, Anay Ajit Deshpande, Michele Polese, Andrea Zanella, Michele Zorzi
Veröffentlicht in: Proceedings of the 23rd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, 2020, Seite(n) 19-26, ISBN 9781450381178
Herausgeber: ACM
DOI: 10.1145/3416010.3423224

SMURF: Reliable Multipath Routing in Flying Ad-Hoc Networks

Autoren: Anay Ajit Deshpande, Federico Chiariotti, Andrea Zanella
Veröffentlicht in: 2020 Mediterranean Communication and Computer Networking Conference (MedComNet), 2020, Seite(n) 1-8, ISBN 978-1-7281-6248-5
Herausgeber: IEEE
DOI: 10.1109/medcomnet49392.2020.9191526

Other (1)

A Primer on Large Intelligent Surface (LIS) for Wireless Sensing in an Industrial Setting

Autoren: Vaca Rubio, Cristian Jesús; Espinosa, Pablo Ramirez; Williams, Robin Jess; Kansanen, Kimmo; Tan, Zheng-Hua; De Carvalho, Elisabeth; Popovski, Petar
Veröffentlicht in: Vaca Rubio , C J , Espinosa , P R , Williams , R J , Kansanen , K , Tan , Z-H , De Carvalho , E & Popovski , P 2021 , A Primer on Large Intelligent Surface (LIS) for Wireless Sensing in an Industrial Setting . in EAI CROWNCOM 2020 - 15th EAI International Conference on Cognitive Radio Oriented Wireless Networks ., 2020
Herausgeber: Springer