Semantics-Native Communication with Contextual Reasoning

• URL: http://arxiv.org/abs/2108.05681v1
• Date: Thu, 12 Aug 2021 12:04:27 GMT
• Title: Semantics-Native Communication with Contextual Reasoning
• Authors: Hyowoon Seo, Jihong Park, Mehdi Bennis, M\'erouane Debbah
• Abstract summary: We propose a novel model of System 1 semantics-native communication (SNC) for generic tasks. We infuse contextual reasoning into SNC such that the speaker locally and iteratively self-communicates with a virtual agent built on the listener's unique way of its semantics. It is also shown that System 2 SNC significantly reduces the SR length without compromising communication reliability.
• Score: 46.2484183677342
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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 stochastic model, we show that the reliability of System 2 SNC increases with the number of meaningful concepts, and derive the expected semantic representation (SR) bit length which quantifies the extracted effective semantics. It is also shown that System 2 SNC significantly reduces the SR length without compromising communication reliability.

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