8 papers
Over-the-Air Semantic Alignment with Stacked Intelligent Metasurfaces
Mario Edoardo Pandolfo, Kyriakos Stylianopoulos, George C. Alexandropoulos +1
Semantic communication systems aim to transmit task-relevant information between devices capable of artificial intelligence, but their performance can degrade when heterogeneous tr…
Colored Markov Random Fields for Probabilistic Topological Modeling
Lorenzo Marinucci, Leonardo Di Nino, Gabriele D'Acunto +3
Probabilistic Graphical Models (PGMs) encode conditional dependencies among random variables using a graph -nodes for variables, links for dependencies- and factorize the joint dis…
Learning Network Sheaves for AI-native Semantic Communication
Enrico Grimaldi, Mario Edoardo Pandolfo, Gabriele D'Acunto +2
Recent advances in AI call for a paradigm shift from bit-centric communication to goal- and semantics-oriented architectures, paving the way for AI-native 6G networks. In this cont…
Semantic Channel Equalization Strategies for Deep Joint Source-Channel Coding
Lorenzo Pannacci, Simone Fiorellino, Mario Edoardo Pandolfo +2
Deep joint source-channel coding (DeepJSCC) has emerged as a powerful paradigm for end-to-end semantic communications, jointly learning to compress and protect task-relevant featur…
Latent Space Alignment for AI-Native MIMO Semantic Communications
Mario Edoardo Pandolfo, Simone Fiorellino, Emilio Calvanese Strinati +1
Semantic communications focus on prioritizing the understanding of the meaning behind transmitted data and ensuring the successful completion of tasks that motivate the exchange of…
RIS-aided Latent Space Alignment for Semantic Channel Equalization
Tomás Hüttebräucker, Mario Edoardo Pandolfo, Simone Fiorellino +2
Semantic communication systems introduce a new paradigm in wireless communications, focusing on transmitting the intended meaning rather than ensuring strict bit-level accuracy. Th…