Timely and Massive Communication in 6G: Pragmatics, Learning, and Inference
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Abstract (arXiv)
5G has expanded the traditional focus of wireless systems to embrace two new connectivity types: ultra-reliable low latency and massive communication. The technology context at the dawn of 6G is different from the past one for 5G, primarily due to the growing intelligence at the communicating nodes. This has driven the set of relevant communication problems beyond reliable transmission towards semantic and pragmatic communication. This paper puts the evolution of low-latency and massive communication towards 6G in the perspective of these new developments. At first, semantic/pragmatic communication problems are presented by drawing parallels to linguistics. We elaborate upon the relation of semantic communication to the information-theoretic problems of source/channel coding, while generalized real-time communication is put in the context of cyber-physical systems and real-time inference. The evolution of massive access towards massive closed-loop communication is elaborated upon, enabling interactive communication, learning, and cooperation among wireless sensors and actuators.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Jun 2023.
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Citing papers per year: 2024: 2; 2025: 0; 2026: 3.
5 papers.
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- 2026Secure Rate-Distortion-Perception: A Randomized Distributed Function Computation Approach for Realismcited by 0
- 2026Risk-Aware Online Conformal State Probingcited by 0
- 2026Risk-Aware Online Conformal State Probing22 Sep 2026
- 2026Secure Rate-Distortion-Perception: A Randomized Distributed Function Computation Approach for Realism22 Apr 2026
- 2026Deep Randomized Distributed Function Computation (DeepRDFC): Neural Distributed Channel Simulation11 Mar 2026
- 2024Multi-level Reliability Interface for Semantic Communications over Wireless Networks7 Jul 2024
- 2024Push- and Pull-based Effective Communication in Cyber-Physical Systems15 Jan 2024