Wireless network emulators are being increasingly used for developing and evaluating new solutions for Next Generation (NextG) wireless networks. However, the reliability of the solutions tested on emulation platforms heavily depends on the precision of the emulation process, model design, and parameter settings. To address, obviate, or minimize the impact of errors of emulation models, in this work, we apply the concept of Digital Twin (DT) to large-scale wireless systems. Specifically, we demonstrate the use of Colosseum, the world's largest wireless network emulator with hardware-in-the-loop, as a DT for NextG experimental wireless research at scale. As proof of concept, we leverage the Channel emulation scenario generator and Sounder Toolchain (CaST) to create the DT of a publicly available over-the-air indoor testbed for sub-6 GHz research, namely, Arena. Then, we validate the Colosseum DT through experimental campaigns on emulated wireless environments, including scenarios concerning cellular networks and jamming of Wi-Fi nodes, on both the real and digital systems. Our experiments show that the DT is able to provide a faithful representation of the real-world setup, obtaining an average similarity of up to 0.986 in throughput and 0.989 in Signal to Interference plus Noise Ratio (SINR).

翻译：无线网络仿真器正越来越多地被用于开发和评估下一代（NextG）无线网络的新解决方案。然而，在仿真平台上测试的解决方案的可靠性高度依赖于仿真过程、模型设计和参数设置的精度。为了解决、避免或最小化仿真模型误差的影响，本文将数字孪生（DT）概念应用于大规模无线系统。具体而言，我们展示了全球最大的硬件在环无线网络仿真器Colosseum作为DT在规模化NextG无线实验研究中的应用。作为概念验证，我们利用信道仿真场景生成器与探测工具链（CaST）为公开可用的6GHz以下频段空中室内试验台Arena创建了DT。随后，我们通过真实与数字系统上的实验活动（包括蜂窝网络场景及Wi-Fi节点干扰场景）验证了Colosseum DT在仿真无线环境中的性能。实验表明，该DT能够忠实再现真实环境配置，在吞吐量和信干噪比（SINR）指标上分别获得了高达0.986和0.989的平均相似度。