Latent Space Alignment for Semantic Channel Equalization

TL;DR

This paper investigates the impact of language mismatch in semantic communication systems, proposing a mathematical framework to measure semantic distortion and a novel method for semantic channel equalization, validated through numerical experiments.

Contribution

It introduces a new mathematical framework for modeling semantic distortion and a novel approach to semantic channel equalization in language-mismatched systems.

Findings

Effective measurement of semantic distortion

Successful semantic channel equalization demonstrated

Improved communication robustness in language mismatch scenarios

Abstract

We relax the constraint of a shared language between agents in a semantic and goal-oriented communication system to explore the effect of language mismatch in distributed task solving. We propose a mathematical framework, which provides a modelling and a measure of the semantic distortion introduced in the communication when agents use distinct languages. We then propose a new approach to semantic channel equalization with proven effectiveness through numerical evaluations.