用量子传感从无线信号中学习环境，无需部署时测量信道。
Learning from Radio using Variational Quantum RF Sensing
- 用量子电路优化量子传感器探测射频场，感知环境变化。
- 实验显示其在弱信号和遮挡下仍有效，且所需信息少于传统方法。
- 适合对低功耗、隐蔽性强的智能系统研发者参考。
在现代无线网络中，无线电波不仅传输数据，其对物理环境的敏感性也使其成为获取世界信息的强大工具。本文研究一种利用量子传感探针的智能体，通过量子电路优化，在射频电磁场中交互并学习环境信息。使用射线追踪生成的数据训练量子电路与学习模型，并在真实条件下完成定位任务的大量实验。结果表明，利用量子传感器从无线信号中学习，可实现无需部署时信道测量的智能系统，对弱信号和遮挡信号仍保持敏感，并在信息量严格低于经典基线的情况下完成环境感知。
原文摘要 · Abstract (English)
In modern wireless networks, radio channels serve a dual role. Whilst their primary function is to carry bits of information from a transmitter to a receiver, the intrinsic sensitivity of transmitted signals to the physical structure of the environment makes the channel a powerful source of knowledge about the world. In this paper, we consider an agent that learns about its environment using a quantum sensing probe, optimised using a quantum circuit, which interacts with the radio-frequency (RF) electromagnetic field. We use data obtained from a ray-tracer to train the quantum circuit and learning model and we provide extensive experiments under realistic conditions on a localisation task. We show that using quantum sensors to learn from radio signals can enable intelligent systems that require no channel measurements at deployment, remain sensitive to weak and obstructed RF signals, and can learn about the world despite operating with strictly less information than classical baselines.
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。