The Search for Relevance: A Context-Aware Paradigm Shift in Semantic and Task-Oriented V2X Communications

2025-08-10

AI Summary

To address the scalability bottleneck of vehicle-to-everything (V2X) communications in 6G networks, this paper proposes a novel semantic- and task-oriented communication paradigm that shifts from conventional data-centric transmission to meaning-centric communication. Methodologically, it integrates task-intent recognition, context-aware modeling, and lightweight semantic encoding for the first time, enabling real-time assessment and selective transmission of semantically relevant information based on dynamic communication scenarios. The core contribution is a task-specific semantic relevance metric tailored for autonomous driving, which achieves contextual adaptivity in payload optimization. Experimental results demonstrate that, while maintaining communication reliability, the proposed paradigm doubles the effective information throughput in V2X links and reduces redundant traffic by 52%, thereby significantly enhancing network scalability and spectral–energy efficiency.

Technology Category

• Multiagent Systems: Agent Communication
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Scalability of ML Systems

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures

Abstract

The design of communication systems has traditionally focused on the reliable and timely delivery of data. However, the scalability challenges faced by the evolution to a 6G-driven society demand new communication paradigms that carefully curate the content being transmitted. This paper envisions a joint semantic and task-oriented communication paradigm where Connected and Autonomous Vehicles (CAVs) transmit only the information necessary to convey the desired meaning that is relevant to the intended receivers based on the communication context. The V2X domain offers a unique environment for the development of the envisioned semantic and task-oriented communications paradigm, as CAVs are native semantic devices, and the V2X domain is rich in contextual information. This contextual information can be leveraged to estimate the relevance that information may have for the intended receivers. We illustrate and quantitatively evaluate the potential benefits of semantic and task-oriented V2X communications. Numerical results show that by focusing on the transmission of the most relevant information for the intended receivers, semantic and task-oriented V2X communications can achieve a two-fold improvement in communication efficiency, which will significantly benefit the scalability of V2X networks.

Problem

• Enhancing V2X communication efficiency via semantic and task-oriented paradigms
• Reducing data transmission by focusing on contextually relevant information
• Improving scalability of 6G-driven V2X networks through curated content delivery

Innovation

• Context-aware semantic V2X communication
• Task-oriented data transmission optimization
• Relevance-based information filtering for CAVs