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These challenges are intensified by the increasing range of applications such as collaborative robotics, full industrial automation, real-time digital twinning, and immersive virtual reality, all while ensuring economic and ecological sustainability. To meet these demands, 6G-MIRAI aims to: develop advanced multi-antenna technologies like user-centric cell-free massive MIMO, address the practical limitations of AI/ML implementation in wireless communications and enable scalable, energy-efficient network solutions.  6G-MIRAI-HARMONY is structured around five Research and Technology Items (RTIs) to achieve its objectives:       Develop realistic models and datasets to serve as the foundation for innovative technological solutions.  Focus on enabling AI/ML techniques for key physical layer components, ensuring reliability, robustness, and scalability.  Explore AI-driven solutions for efficient coordination of physical layer components, higher-layer functions, and control planes, especially in cell-free networks.  Provide design guidelines for AI-ready 6G-RAN architectures  Investigate methodologies for data management, testing, and validation        The presentation will given an overview of the project (consortium partners, objectives) and outline the project’s research & standards baselines and target landing zones."],"publicationDate":"2025-07-09","publisher":"Zenodo","embargoEndDate":null,"sources":null,"formats":null,"contributors":["Ley, Tobias","Garrido Cavalcante, Renato Luis","Nakao, Akihiro"],"coverages":null,"bestAccessRight":{"code":"c_abf2","label":"OPEN","scheme":"http://vocabularies.coar-repositories.org/documentation/access_rights/"},"container":null,"documentationUrls":null,"codeRepositoryUrl":null,"programmingLanguage":null,"contactPeople":null,"contactGroups":null,"tools":null,"size":null,"version":null,"geoLocations":null,"id":"doi_dedup___::83eb0a5b0e3feb6c8809ebfff35a1b20","originalIds":["50|datacite____::83eb0a5b0e3feb6c8809ebfff35a1b20","10.5281/zenodo.16680180","50|datacite____::a8f4d6f615d166af2e861b65015cef9e","10.5281/zenodo.16680181","50|od______2659::a8f4d6f615d166af2e861b65015cef9e","oai:zenodo.org:16680181"],"pids":[{"scheme":"doi","value":"10.5281/zenodo.16680180"},{"scheme":"doi","value":"10.5281/zenodo.16680181"}],"dateOfCollection":null,"lastUpdateTimeStamp":null,"indicators":{"citationImpact":{"citationCount":0.0,"influence":2.2251732E-9,"popularity":2.342466E-9,"impulse":0.0,"citationClass":"C5","influenceClass":"C5","impulseClass":"C5","popularityClass":"C5"}},"projects":[{"id":"corda_____he::495834d3820eb5bbaf70b8512cfb32f5","code":"101192369","acronym":"6G-MIRAI","title":"Machine Intelligence based Radio Access Infrastructure","funder":"European Commission","pids":[{"scheme":"doi","value":"10.3030/101192369"}]}],"organizations":[{"legalName":"Apple (Germany)","acronym":"Apple (Germany)","id":"openorgs____::fb2dd16e7abd646108a45fd0e55a93c7","pids":[{"scheme":"ISNI","value":"0000000417920057"},{"scheme":"wikidata","value":"Q29000247"},{"scheme":"ROR","value":"https://ror.org/03fjbw519"},{"scheme":"Wikidata","value":"Q29000247"},{"scheme":"GRID","value":"grid.474343.3"}]}],"communities":[{"code":"eosc","label":"EOSC","provenance":null}],"collectedFrom":[{"key":"openaire____::9e3be59865b2c1c335d32dae2fe7b254","value":"Datacite"},{"key":"opendoar____::358aee4cc897452c00244351e4d91f69","value":"ZENODO"}],"instances":[{"pids":[{"scheme":"doi","value":"10.5281/zenodo.16680180"}],"license":"CC BY","type":"Article","urls":["https://dx.doi.org/10.5281/zenodo.16680180"],"publicationDate":"2025-07-09","refereed":"nonPeerReviewed","hostedBy":{"key":"opendoar____::358aee4cc897452c00244351e4d91f69","value":"ZENODO"},"collectedFrom":{"key":"openaire____::9e3be59865b2c1c335d32dae2fe7b254","value":"Datacite"}},{"pids":[{"scheme":"doi","value":"10.5281/zenodo.16680181"}],"license":"CC BY","type":"Article","urls":["https://dx.doi.org/10.5281/zenodo.16680181"],"publicationDate":"2025-07-09","refereed":"nonPeerReviewed","hostedBy":{"key":"opendoar____::358aee4cc897452c00244351e4d91f69","value":"ZENODO"},"collectedFrom":{"key":"openaire____::9e3be59865b2c1c335d32dae2fe7b254","value":"Datacite"}},{"pids":[{"scheme":"doi","value":"10.5281/zenodo.16680181"}],"alternateIdentifiers":[{"scheme":"oai","value":"oai:zenodo.org:16680181"}],"license":"CC BY","accessRight":{"code":"c_abf2","label":"OPEN","scheme":"http://vocabularies.coar-repositories.org/documentation/access_rights/","openAccessRoute":null},"type":"Conference object","urls":["https://zenodo.org/records/16680181","http://dx.doi.org/10.5281/zenodo.16680181"],"publicationDate":"2025-07-09","refereed":"nonPeerReviewed","hostedBy":{"key":"opendoar____::358aee4cc897452c00244351e4d91f69","value":"ZENODO"},"collectedFrom":{"key":"opendoar____::358aee4cc897452c00244351e4d91f69","value":"ZENODO"}}],"links":[{"header":{"relationType":"resultProject","relationClass":"isProducedBy","relatedIdentifier":"corda_____he::495834d3820eb5bbaf70b8512cfb32f5","relatedRecordType":"project","relationProvenance":"sysimport:crosswalk:repository","trust":"0.9"},"collectedfrom":[{"dsId":"openaire____::3f264f93cf3b0cfc4ede188a6300455c","dsName":"CORDA - COmmon Research DAta Warehouse - Horizon Europe"}],"projectTitle":"Machine Intelligence based Radio Access Infrastructure","code":"101192369","funding":{"funder":{"id":"ec__________::EC","shortname":"EC","name":"European Commission","jurisdiction":{"code":"EU","label":"European Union"},"pid":null},"level0":{"id":"ec__________::EC::HE","description":"Horizon Europe Framework Programme","name":"HE"},"level1":{"id":"ec__________::EC::HE::HORIZON-JU-RIA","description":"HORIZON JU Research and Innovation Actions","name":"HORIZON-JU-RIA"},"level2":{"id":null,"description":null,"name":null}},"startDate":"2025-04-01","endDate":"2028-03-31"}],"otherTitles":null,"inDiamondJournal":false,"green":true,"isGreen":true,"isInDiamondJournal":false}