2 citations · 2 across the 5 of their papers we have counts for
6 papers
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…
Frame-Based Zero-Shot Semantic Channel Equalization for AI-Native Communications
Simone Fiorellino, Claudio Battiloro, Emilio Calvanese Strinati +1
In future AI-native wireless networks, the presence of mismatches between the latent spaces of independently designed and trained deep neural network (DNN) encoders may impede mutu…
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…
Topological Neural Networks over the Air
Simone Fiorellino, Claudio Battiloro, Paolo Di Lorenzo
Topological neural networks (TNNs) are information processing architectures that model representations from data lying over topological spaces (e.g., simplicial or cell complexes)…
Relative Representations of Latent Spaces enable Efficient Semantic Channel Equalization
Tomás Hüttebräucker, Simone Fiorellino, Mohamed Sana +2
In multi-user semantic communication, language mismatche poses a significant challenge when independently trained agents interact. We present a novel semantic equalization algorith…