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pro vyhledávání: '"Chaaya, Charbel Bou"'
In this work, we propose a novel data-driven machine learning (ML) technique to model and predict the dynamics of the wireless propagation environment in latent space. Leveraging the idea of channel charting, which learns compressed representations o
Externí odkaz:
http://arxiv.org/abs/2409.10045
In this paper, we investigate the problem of robust Reconfigurable Intelligent Surface (RIS) phase-shifts configuration over heterogeneous communication environments. The problem is formulated as a distributed learning problem over different environm
Externí odkaz:
http://arxiv.org/abs/2306.01306
Reconfigurable Intelligent Surfaces (RIS) are considered a key enabler to achieve the vision of Smart Radio Environments, where the propagation environment can be programmed and controlled to enhance the efficiency of wireless systems. These surfaces
Externí odkaz:
http://arxiv.org/abs/2301.09096
Reconfigurable Intelligent Surfaces (RIS) have recently emerged as a hot research topic, being widely advocated as a candidate technology for next generation wireless communications. These surfaces passively alter the behavior of propagation environm
Externí odkaz:
http://arxiv.org/abs/2301.09093
Akademický článek
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