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 accuracy of up to 92.5% in throughput and 80% 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在很大程度上取决于仿真过程、模型设计和参数设置的精度。为了处理、避免或最小化仿真模型误差的影响，在本工作中，我们将数字孪生（DT）的概念应用于大规模无线系统。具体而言，我们展示了科洛西姆——全球最大的带有硬件在环的无线网络仿真器——作为大规模NextG实验性无线研究数字孪生体的应用。作为概念验证，我们利用信道仿真场景生成器和探测工具链（CaST）为Arena（一个公开可用的6 GHz以下频段的室内空中测试平台）创建了数字孪生。随后，我们通过在真实和数字系统上开展关于蜂窝网络及Wi-Fi节点干扰等场景的无线环境仿真实验，对科洛西姆数字孪生进行了验证。实验结果表明，该数字孪生能够忠实再现真实环境设置，在吞吐量和信号与干扰加噪声比（SINR）指标上分别获得了高达92.5%和80%的平均准确度。