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Titre : New Baseband Architectures Using Machine Learning and Deep Learning in the Presence of Nonlinearities and Dynamic Environment
Date : 13 mars 2024
Heure: 13:00
Résumé : Throughout the course of this research, we leveraged these potential tools to advance the state-of-the-art in receiver design for vehicular communication networks. In this manner, we delved into the characteristics of wireless channel estimation and the mitigation of nonlinear distortions, recognizing these as significant factors in the communication system performance. To this end, we propose new methods and flexible receivers, based on hybrid approaches that combine mathematical models and machine learning techniques, taking advantage of the unique characteristics of the vehicular channel to favor accurate estimation. Our analysis covers both conventional wireless communications waveform and a promising 6G waveform, targeting the comprehensiveness of our approach. The results of the proposed approaches are promising, characterized by substantial enhancements in performance and noteworthy reductions in system complexity.
Lieu : 100% en ligne via l'application Teams. En effet, les seuls participants qui peuvent être présents en personne sont les superviseurs du côté brésilien et le président du jury.