Distributed Semantic Alignment over Interference Channels: A Game-Theoretic Approach

2026-03-06

AI Summary

This work addresses the semantic mismatch arising from discrepancies between device logic and internal representations in AI-driven systems, as well as the degradation of multi-user communication performance under interfering channels. It proposes the first unified framework that jointly models semantic alignment and MIMO transmission as a distributed non-cooperative game, wherein each user acts as a self-interested agent simultaneously optimizing its transmission strategy and semantic representation. By integrating game theory, MIMO signal processing, and latent space alignment techniques, the study derives sufficient conditions for the existence of a Nash equilibrium and obtains a closed-form solution. Experimental results demonstrate that the proposed approach effectively balances information compression, interference suppression, semantic alignment, and downstream task performance, significantly enhancing semantic communication efficiency.

Technology Category

• Multiagent Systems: Agent Communication
• Search and Optimization: Learning to Search
• Machine Learning: Multimodal Learning

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

Semantic communication acts as a key enabler for effective task execution in AI-driven systems, prioritizing the extraction of the underlying meaning before transmission. However, when devices rely on different logic and internal representations, semantic mismatches may arise, potentially hindering mutual understanding and effectiveness of communication. Furthermore, in interference channel environments, the coexistence of multiple devices introduce a significant degradation due to the presence of multi-user-interference. To address these challenges, in this paper we formulate the joint optimization of linear Multiple-Input-Multiple-Output (MIMO) transceivers as a distributed non-cooperative game, enabling a closed-form solution that effectively addresses semantic coexistence and latent space misalignment. We derive sufficient conditions for the existence of a Nash Equilibrium (NE), considering multiple point-to-point MIMO channels, with corresponding users modeled as selfish players optimizing their transmission and semantic alignment strategies. Numerical results substantiate the proposed approach in goal-oriented semantic communication by highlighting crucial trade-offs between information compression, interference mitigation, semantic alignment, and task performance.

Problem

• semantic alignment
• interference channels
• semantic mismatch
• multi-user interference
• distributed communication

Innovation

• Semantic Communication
• Interference Channels
• Game Theory
• MIMO Transceivers
• Nash Equilibrium