we 're essentially proposing a JEPA-aided multimodal semantic ISAC system, where semantic embeddings are transmitted instead of raw data, enhancing communication efficiency and enabling more proactive, context-aware sensing and decision-making across multiple modalities.
What makes our contribution different:
- JEPA-based Semantic Embeddings: The focus on leveraging JEPA for extracting semantic embeddings and transmitting them across distributed nodes distinguishes your system from traditional ISAC approaches, which rely heavily on raw data transmission.
- Multimodal Intuitive Sensing: our framework not only integrates multiple sensing modalities but does so in a way that enables nodes to anticipate, adapt, and offer proactive assistance—something current systems lack.
- Reduced Communication Overhead: By focusing on semantic embedding transmission rather than raw data, our framework offers reduced bandwidth usage and computational load, which is critical for real-time, distributed environments.
we did not refer to raising privacy concerns.
multimodal semantic communication enable multimodal (intuitive) sensing
semantic transmission / coding encoding is eliminated due to multimodal setting?
性能比較のため、Baselineは多分入りません？なぜなら、我々の最終目的はRaw data reconstructionではなく、intuitive sensingでありますから、これは従来のsemantic communicationと一番違うところだと思います）