Latent Space Alignment for Semantic Channel Equalization
This addresses the challenge of enabling effective communication between agents with different languages in distributed task-solving systems, representing an incremental improvement in semantic communication methods.
The paper tackled the problem of language mismatch in semantic communication systems by proposing a mathematical framework to model and measure semantic distortion, and introduced a new semantic channel equalization approach validated through numerical evaluations.
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.