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

Deniz Gündüz, Federico Chiariotti, Kaibin Huang, Anders E. Kalør, Szymon Kobus, Petar Popovski
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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.
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6G时代的及时和大规模传播:语用学、学习和推理
5G扩展了无线系统的传统重点,包括两种新的连接类型:超可靠的低延迟和大规模通信。6G初期的技术背景与过去的5G不同,主要是由于通信节点的智能化程度不断提高。这使得一系列相关的交际问题从可靠的交际转向语义和语用交际。本文从这些新发展的角度阐述了低延迟和大规模通信向6G的演变。首先,语义/语用交际问题是通过与语言学的类比来提出的。我们详细阐述了语义通信与源/信道编码的信息理论问题的关系,而广义实时通信则放在网络物理系统和实时推理的背景下。详细阐述了大规模接入向大规模闭环通信的演变,实现了无线传感器和执行器之间的交互通信、学习和合作。
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