Modulation Recognition IQ Samples Across Heterogeneous Sensors

In this paper, we design and present a testbed implementation and the resulting dataset for modulation recognition from real-world imperfect scans. We describe our efforts to build a testbed of heterogeneous spectrum sensors (low-cost RTL-SDR and mid-cost USRP) and a controlled transmitter in order to facilitate real-world data collection for modulation recognition from partial and biased scans. The testbed allows data collection, in the form of IQ samples, across five common modulation types (BPSK, QPSK, 8PSK, 16-QAM, 64-QAM) and with a controlled bandwidth overlap, 50% and 100%, between the transmitter and sensor. Using the data collected from the testbed, we then demonstrate modulation recognition from real-world, low-cost and imperfect scans. Our dataset is positioned to facilitate new research into signal recognition from partial and biased real-world spectrum data. Furthermore, the data can also facilitate research on the applicability of various sensor platforms to support real-world spectrum characterization.

搜集汇总

背景与挑战

背景概述

该数据集包含通过异构传感器（RTL-SDR和USRP）收集的真实世界调制识别IQ样本，覆盖五种常见调制类型（BPSK、QPSK、8PSK、16-QAM、64-QAM）和两种带宽重叠水平（50%和100%），旨在支持从部分和偏置频谱数据中进行信号识别的研究，并评估不同传感器平台在频谱表征中的适用性。