18 papers
Compositional Semantic Communication for Physical AI: Category Theory Meets Game Theory
Christo Kurisummoottil Thomas, Walid Saad, Emilio Calvanese Strinati
Physical artificial intelligence (AI) systems involve distributed sensing agents with embedded AI models that must coordinate to perceive, reason, and act in networked environments…
Game-Theoretic Latent Space Alignment for Multi-user Semantic MIMO Communications
Giuseppe Di Poce, Mattia Merluzzi, Emilio Calvanese Strinati +1
Semantic communications enable AI-native wireless systems by mapping raw data into compressed task-oriented latent representations. However, independently trained agents often rely…
Resilience Characterization of AI-Native Wireless Receivers via Persistent Homology
Christo Kurisummoottil Thomas, Emilio Calvanese Strinati
AI-native wireless receivers based on deep learning exhibit remarkable performance under stationary channel conditions, yet their resilience to distributional shifts remains poorly…
Distributed Semantic Alignment over Interference Channels: A Game-Theoretic Approach
Giuseppe Di Poce, Mattia Merluzzi, Emilio Calvanese Strinati +1
Semantic communication acts as a key enabler for effective task execution in AI-driven systems, prioritizing the extraction of the underlying meaning before transmission. However,…
Federated Latent Space Alignment for Multi-user Semantic Communications
Giuseppe Di Poce, Mario Edoardo Pandolfo, Emilio Calvanese Strinati +1
Semantic communication aims to convey meaning for effective task execution, but differing latent representations in AI-native devices can cause semantic mismatches that hinder mutu…
Semantic Waveforms for AI-Native 6G Networks
Nour Hello, Mohamed Amine Hamoura, Francois Rivet +1
In this paper, we propose a semantic-aware waveform design framework for AI-native 6G networks that jointly optimizes physical layer resource usage and semantic communication effic…