用无线信道图谱提升动态数字孪生中的定位精度。
Chartwin: a Case Study on Channel Charting-aided Localization in Dynamic Digital Network Twins
- 将信道图谱与动态数字网络孪生结合，实现空间一致的无线地图构建。
- 静态环境下定位误差约4.5米，动态环境下约6米。
- 适合研究无线定位、数字孪生与智能通信系统的人参考。
无线通信系统可从空间一致的无线信道表示中获益，从而高效完成各类通信任务。为此，信道图谱作为一种有效的无监督学习技术，已被提出以实现局部和全局一致的无线电地图。本文提出Chartwin，作为将面向定位的信道图谱与动态数字网络孪生（DNT）集成的案例研究。数值结果表明，半监督信道图谱在构建所考虑扩展城市环境的空间一致图谱方面表现出显著性能。该方法在静态DNT下实现约4.5米的定位误差，在动态DNT下约为6米，推动了基于DNT的信道图谱与定位技术的发展。
原文摘要 · Abstract (English)
Wireless communication systems can significantly benefit from the availability of spatially consistent representations of the wireless channel to efficiently perform a wide range of communication tasks. Towards this purpose, channel charting has been introduced as an effective unsupervised learning technique to achieve both locally and globally consistent radio maps. In this letter, we propose Chartwin, a case study on the integration of localization-oriented channel charting with dynamic Digital Network Twins (DNTs). Numerical results showcase the significant performance of semi-supervised channel charting in constructing a spatially consistent chart of the considered extended urban environment. The considered method results in $\approx$ 4.5 m localization error for the static DNT and $\approx$ 6 m in the dynamic DNT, fostering DNT-aided channel charting and localization.
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