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Deep Learning-Enabled Text Semantic Communication under Interference: An Empirical Study
Tilahun M. Getu, Georges Kaddoum, Mehdi Bennis
At the confluence of 6G, deep learning (DL), and natural language processing (NLP), DL-enabled text semantic communication (SemCom) has emerged as a 6G enabler since it minimizes b…
Language-Oriented Communication with Semantic Coding and Knowledge Distillation for Text-to-Image Generation
Hyelin Nam, Jihong Park, Jinho Choi +2
By integrating recent advances in large language models (LLMs) and generative models into the emerging semantic communication (SC) paradigm, in this article we put forward to a nov…
Joint Semantic-Native Communication and Inference via Minimal Simplicial Structures
Qiyang Zhao, Hang Zou, Mehdi Bennis +3
In this work, we study the problem of semantic communication and inference, in which a student agent (i.e. mobile device) queries a teacher agent (i.e. cloud sever) to generate hig…
Making Sense of Meaning: A Survey on Metrics for Semantic and Goal-Oriented Communication
Tilahun M. Getu, Georges Kaddoum, Mehdi Bennis
Semantic communication (SemCom) aims to convey the meaning behind a transmitted message by transmitting only semantically-relevant information. This semantic-centric design helps t…
Performance Analysis of ML-based MTC Traffic Pattern Predictors
David E. Ruiz-Guirola, Onel L. A. Lopez, Samuel Montejo-Sanchez +2
Prolonging the lifetime of massive machine-type communication (MTC) networks is key to realizing a sustainable digitized society. Great energy savings can be achieved by accurately…
Computation and Privacy Protection for Satellite-Ground Digital Twin Networks
Yongkang Gong, Haipeng Yao Xiaonan Liu, Mehdi Bennis +2
Satellite-ground integrated digital twin networks (SGIDTNs) are regarded as innovative network architectures for reducing network congestion, enabling nearly-instant data mapping f…