不发探测包就能用Wi-Fi做高精度感知，还能保持网络畅通。
UniFi: Combining Irregularly Sampled CSI from Diverse Communication Packets and Frequency Bands for Wi-Fi Sensing
- 直接利用多频段真实通信包的不规则采样信道状态信息
- 在真实数据集上达到顶尖感知精度，模型小且不降低通信速度
- 适合想在不干扰网络前提下做无线感知的研究者和工程师
现有Wi-Fi感知系统依赖高频探测包提取信道状态信息（CSI），导致通信性能下降且难以部署。尽管感知与通信一体化（ISAC）是未来方向，但现有方案仍需额外注入探测包，仅利用数据帧的CSI。我们提出UniFi，首个无需侵入式包注入的Wi-Fi ISAC框架，直接利用多频段、多样通信包中的不规则采样CSI。UniFi集成信道状态信息清洗流程，统一异构包数据并去除突发冗余，并采用时间感知注意力模型，直接学习非均匀采样序列，无需重采样。我们进一步构建了首个真实双频段通信流量中不规则采样CSI的数据集CommCSI-HAR。在该数据集及四个公开基准上的大量评估表明，UniFi在保持通信吞吐量的同时，实现当前最优感知精度，且模型体积紧凑。
原文摘要 · Abstract (English)
Existing Wi-Fi sensing systems rely on injecting high-rate probing packets to extract channel state information (CSI), leading to communication degradation and poor deployability. Although Integrated Sensing and Communication (ISAC) is a promising direction, existing solutions still rely on auxiliary packet injection because they exploit only CSI from data frames. We present UniFi, the first Wi-Fi-based ISAC framework that fully eliminates intrusive packet injection by directly exploiting irregularly sampled CSI from diverse communication packets across multiple frequency bands. UniFi integrates a CSI sanitization pipeline to harmonize heterogeneous packets and remove burst-induced redundancy, together with a time-aware attention model that learns directly from non-uniform CSI sequences without resampling. We further introduce CommCSI-HAR, the first dataset with irregularly sampled CSI from real-world dual-band communication traffic. Extensive evaluations on this dataset and four public benchmarks show that UniFi achieves state-of-the-art accuracy with a compact model size, while fully preserving communication throughput.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。