Semantics-Native Communication with Contextual Reasoning
Hyowoon Seo, Jihong Park, Mehdi Bennis, M\'erouane Debbah

TL;DR
This paper introduces a novel semantics-native communication model inspired by human communication, incorporating contextual reasoning to improve semantic extraction and reduce communication overhead.
Contribution
It proposes a stochastic model of semantics-native communication with a new System 2 approach that integrates contextual reasoning for enhanced semantic efficiency.
Findings
Reliability of System 2 SNC increases with more meaningful concepts.
System 2 SNC reduces semantic representation length significantly.
Expected SR bit length quantifies effective semantics extracted.
Abstract
Spurred by a huge interest in the post-Shannon communication, it has recently been shown that leveraging semantics can significantly improve the communication effectiveness across many tasks. In this article, inspired by human communication, we propose a novel stochastic model of System 1 semantics-native communication (SNC) for generic tasks, where a speaker has an intention of referring to an entity, extracts the semantics, and communicates its symbolic representation to a target listener. To further reach its full potential, we additionally infuse contextual reasoning into SNC such that the speaker locally and iteratively self-communicates with a virtual agent built on the physical listener's unique way of coding its semantics, i.e., communication context. The resultant System 2 SNC allows the speaker to extract the most effective semantics for its listener. Leveraging the proposed…
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Taxonomy
TopicsWireless Signal Modulation Classification · DNA and Biological Computing · Robotics and Automated Systems
