D2.3: Techno-economic Analysis and Data Set Definition

This deliverable details the methodologies developed in DESIRE6G to identify and define datasets. It includes a tailored methodology especially designed for demo use cases, as well as an alternative methodology for those datasets generated as the results of different DESIRE6G components. Moreover, the deliverable presents several techno-economic studies oriented to show the benefits in terms of cost reduction (related to CAPEX and OPEX) and expected revenue/income increase by adopting DESIRE6G innovations to improve current benchmarking infrastructures and technologies. Regarding these techno-economic analysis contents, the deliverable presents some chapters where infrastructure, traffic, and service analysis coming from real operator measurements and data are provided as starting reference point. Then, studies organized by individual chapters are focused on one or more DESIRE6G architectural components, with the objective to evaluate the potential benefits in both qualitative and quantitative terms.

Authors:

Anestis Dalgkitsis, Cyril Hsu, Chrysa Papagianni (UVA), Juan José Vegas, Olmos, Amelia Pakouline-Navarro (NV), Francesco Paolucci, Michelangelo Guaitolini (CNIT), Attila Mihály, Gergely Pongrácz (ERI-HU),Michele Gucciardo, Roberto Gonzalez (NEC), Anastassios Nanos, George Ntoutsos, Charalampos Mainas, Panagiotis Mavrikos, Christos Panagiotou (NUBIS), Chathuranga Weeraddana, Chamith Mawela Mudiyanselage (UOU), Luis Velasco, Marc Ruiz, Jaume Comellas, Davide Careglio, Josep Prat (UPC), Sándor Laki (ELTE), Andrea Sgambelluri (SSSA), Mark Angoustures, Vincent Lefebvre (TSS), Miguel A. Carnero Fernández, Luis M. Contreras Murillo, Marta Blanco Caamaño (TID), Merve Saimler, Sultan Ertaş (EBY), Simon Pryor, Stephen Parker (ACC)