The procedure of classifying a detected signal’s modulation scheme with no a priori information is known as automatic modulation classification (AMC). AMC has presented numerous contributions toward civilian and military applications. However, in the scientific literature, designing automatic modulation classifiers has been limited to a single particular simulated environment in most cases of study. Hence, the performance of such classifiers lacks: 1) reliability in real-world environments and 2) multivariate environment analysis for AMC operation in dissimilar surroundings. These two reasons represent a significant obstacle to the real-world implementation of such classifiers. Therefore, in this research, we present our contribution to remove these obstacles by generating an emulated signal reference dataset named MIMOSigRef-SD. It includes a wide variety of signal streams modulated by different digital modulation schemes, such as M-QAM, MIL-STD-188-110 B/C standard-specific QAM, M-PSK, M-APSK, DVB-S2/S2X/SH standard-specific APSK, and M-PAM with different modulation orders, each with different multiple-input multiple-output (MIMO) system configurations in order to provide an extensive signal reference. Each signal is also exposed to the realistic impact of different channel models at 2450 MHz, specifically Vehicular-A/B, Pedestrian-A/B, and the Butler, through a channel emulator. This signal reference includes the randomly generated transmit signals, characteristics of the emulated environments, and the recorded received symbols. This enables the dataset to be highly applicable to applications beyond AMC as well. In general, this signal reference can help analyze, evaluate, and design any other radio frequency transceiver tasks under realistic environmental effects. We also validate the elements of the signal reference by comparing the emulation and simulation bit error rate of the designed communication system.

中文翻译：

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用于射频信号处理研究的空间分集MIMO数据集

不带检测信号的调制方案的分类过程 先验该信息称为自动调制分类（AMC）。AMC为民用和军事应用做出了许多贡献。然而，在科学文献中，在大多数研究情况下，设计自动调制分类器已限于单个特定的模拟环境。因此，此类分类器的性能缺乏：1）在现实环境中的可靠性； 2）在不同环境中对AMC操作进行的多元环境分析。这两个原因代表了此类分类器在现实世界中的实施的重大障碍。因此，在这项研究中，我们提出了通过生成名为MIMOSigRef-SD的仿真信号参考数据集来消除这些障碍的贡献。它包括通过不同的数字调制方案调制的各种信号流，例如具有不同调制阶数的M-QAM，MIL-STD-188-110 B / C标准特定的QAM，M-PSK，M-APSK，DVB-S2 / S2X / SH标准特定的APSK和M-PAM，每个都具有不同的多输入多输出（MIMO）系统配置，以便提供广泛的信号参考。通过通道仿真器，每个信号还暴露于2450 MHz的不同通道模型的实际影响，特别是车辆A / B，行人A / B和巴特勒。该信号参考包括随机生成的发射信号，仿真环境的特性以及记录的接收符号。这也使数据集也高度适用于AMC以外的应用程序。通常，该信号参考可以帮助分析，评估，并在现实的环境影响下设计任何其他射频收发器任务。我们还通过比较设计的通信系统的仿真和仿真误码率来验证信号参考的元素。