Replication Data for: Multi-Dimensional Wireless Signal Identification Based on Support Vector Machines

<p>The dataset includes spectral correlation function (SCF) estimations by FFT accumulation method (FAM) for totally 4500 signals with 20000 I/Q samples (but only 16384 samples are used). The signals belong to three different cellular communication standards: GSM, WCDMA, and LTE. The signals have been received from different channels with multipath, fading, and noise. </p>

<p>Furthermore, the dataset provides other features such as Fast Fourier Transform (FFT), Autocorrelation (ACF), and Power Spectral Density (PSD) in linear scale. </p>

<p>The dataset can be used to validate the designed classifier model aiming to identify cellular communication signals.</p>

<p>For each signal, the dimension of SCF estimate (alpha domain profile maximizing over spectral frequency) is 1*32769. There are four train sets which must be used together (SCF_train1.mat, SCF_train2.mat, SCF_train3.mat, and SCF_train4.mat). Four train sets for each feature have 3000 signals totally, and two test sets for each feature have 1500.</p>

<p>The label of the cellular communication standards are given in dataset as follows:</p>

<p>WCDMA -> 0 </p>
<p>LTE -> 1 </p>
<p>GSM -> 2 </p>

<p>The compressed file includes: </p>

<p>1. ACF Folder </p>
<p>2. FFT Folder </p>
<p>3. PSD Folder </p>
<p>4. SCF Folder </p>

<p>Each folder above consists of two folder: Test and Train. The test set is located in the Test folder as two parts and the train set is located in the Train folder as four parts. </p>

<p>The contents of .mat files:</p>

<p>training_class_k : denotes class labels corresponding to the training_data_k, its dimension is 750*1 double </p>
<p>training_data_k : includes the kth quarter of the training data, its dimension is 750*32769 double </p>

<p>test_class_k : denotes class labels corresponding to the test_data_k, its dimension is 750*1 double </p>
<p>test_data_k : includes the kth half of the test data, its dimension is 750*32769 double </p>

<p>The dataset has been used for the paper "<b>Multi-Dimensional Wireless Signal Identification Based on Support Vector Machines</b>" submitted for possible publication in IEEE Access. Please cite this paper, if you use the dataset.</p>