Datasets of Indoor Wireless Channel Measurements for Machine Learning Applications

This is a simple dataset of raw IQ measurements on a point-to-point wireless indoor channel, captured in a static laboratory environment. A sequence of random symbols (either QPSK symbols or random Gaussian symbols) are passed through a raised-root-cosine filter and modulated to different frequencies (433 MHz, 708 MHz, 2450 MHz). These measurements are carried out for varying signal-to-noise conditions (approximately 0 dB, 10 dB, 20 dB, estimated pre-measurement). These datasets may be used, for example, for data-driven channel modeling with state-of-the-art AI and machine learning algorithms (e.g., generative adversarial networks), for validating conventional channel models against real measurements, or for investigating the properties of real wireless channels. A detailed description is provided in the file README.pdf<br>本数据集为静态实验室环境下采集的点对点无线室内信道原始IQ测量基础数据集。一系列随机符号（含正交相移键控（QPSK）符号与随机高斯符号）经升余弦根滤波器（raised-root-cosine filter）处理后，被调制至433 MHz、708 MHz、2450 MHz三个不同载波频率。本次测量针对多种信噪比条件开展，预估计的信噪比分别约为0 dB、10 dB、20 dB。该数据集可应用于多类研究场景：例如，结合前沿人工智能与机器学习算法（如生成对抗网络（generative adversarial networks））开展数据驱动的信道建模；基于实测数据验证传统信道模型的准确性；或探究真实无线信道的传输特性。数据集的详细说明详见附带的README.pdf文件。