Timely and Massive Communication in 6G: Pragmatics, Learning, and Inference

TL;DR

This paper explores the evolution of 6G communication systems emphasizing semantic and pragmatic communication, real-time inference, and massive closed-loop interactions, driven by increased intelligence at nodes and new connectivity needs.

Contribution

It provides a comprehensive perspective on 6G evolution, linking linguistic concepts to communication theory and highlighting the shift towards intelligent, interactive, and semantic communication paradigms.

Findings

Semantic communication relates to source/channel coding in information theory.

Generalized real-time communication is crucial for cyber-physical systems.

Massive access evolves into massive closed-loop communication enabling interaction.

Abstract

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.