dataCollect.md

Data Collection with Jamming for Spectrogram Analysis

Steps Overview

• Transmit a Continuous Tone from grid02 (Baseline Signal)
• Set Up IQ Data Logging on Receiver Node grid01
• Introduce Jamming with Varying Intensities on grid03
• Stop Data Logging and Transfer the File to Your Local Machine
• Generate Spectrogram Snippets from the Collected IQ Data

Step 1: Transmit a Continuous Tone (Baseline Signal) Log into grid02.

Start Tone Transmission:

uhd_siggen -f 1.305e9 -s 1e6 -g 20 --sine -x 10e3

Frequency: 1.305 GHz Sample Rate: 1 MHz Gain: 20 dB Leave this running throughout the data collection process.

Step 2: Set Up IQ Data Logging on Receiver (grid01) Log into grid01.

Start IQ Data Logging using uhd_rx_cfile to capture 60 seconds of IQ data:

uhd_rx_cfile --freq 1.305e9 --samp-rate 1e6 --gain 20 /home/mt3429/logsFinal/iq_data_with_jamming.bin

Output file: /home/mt3429/logsFinal/iq_data_with_jamming.bin Let this command run for the entire 60 seconds while you introduce jamming from grid03.

##Step 3: Introduce Jamming with Varying Intensities on grid03 Log into grid03.

Run DragonJammer to introduce jamming in 20-second increments with increasing strength:

First 20 Seconds

./DragonJammer -f 1.305e9 -b 1e6 -G 5 -t 20 (Low Jamming) Next 20 Seconds

./DragonJammer -f 1.305e9 -b 2e6 -G 15 -t 20 (Medium Jamming) Final 20 Seconds

./DragonJammer -f 1.305e9 -b 4e6 -G 30 -t 20 (High Jamming) Frequency: 1.305 GHz

Bandwidths: 1 MHz, 2 MHz, 4 MHz (progressively)

Gains: 5, 15, and 30 dB (progressively)

This creates a 60-second capture with varying jamming intensities.

Step 4: Stop IQ Data Logging and Transfer to Local Machine Stop uhd_rx_cfile on grid01 after 60 seconds by pressing Ctrl+C.

Verify that the file was saved:

ls -lh /home/mt3429/logsFinal/iq_data_with_jamming.bin Copy the IQ Data File to Your Local Machine:

scp [email protected]:/home/mt3429/logsFinal/iq_data_with_jamming.bin /path/to/your/local/directory/ Replace /path/to/your/local/directory/ with the actual path where you want to save the file.

Step 5: Generate Spectrogram Snippets with Visible Jamming Levels Set up a Python script to create 60 spectrogram snippets (1 per second) to visualize varying jamming levels.

import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import spectrogram
import os

# Path to your IQ data file with jamming and output directory
file_path = '/Users/matthewtylek/repos/stable-diffusion-research/dataCollect/iq_data_with_jamming.bin'
output_dir = '/Users/matthewtylek/repos/stable-diffusion-research/dataCollect/spectrogram_snippets_jamming'

# Create the output directory if it doesn't exist
os.makedirs(output_dir, exist_ok=True)

# Load the IQ data
iq_data = np.fromfile(file_path, dtype=np.complex64)

# Parameters for spectrogram generation
sample_rate = 1e6  # Sampling rate in Hz
snippet_duration = 1  # Duration of each snippet in seconds
snippet_samples = int(sample_rate * snippet_duration)  # Number of samples per snippet

# Loop through data in chunks and generate spectrograms
for i in range(0, len(iq_data), snippet_samples):
    snippet = iq_data[i:i + snippet_samples]
    
    # Skip if the last chunk is smaller than snippet_samples
    if len(snippet) < snippet_samples:
        break
    
    # Generate the spectrogram
    f, t, Sxx = spectrogram(snippet, fs=sample_rate, nperseg=1024, noverlap=512)
    
    # Plot the spectrogram
    plt.figure(figsize=(10, 6))
    plt.pcolormesh(t, f, 10 * np.log10(Sxx), shading='gouraud')
    plt.ylabel('Frequency [Hz]')
    plt.xlabel('Time [s]')
    plt.colorbar(label='Intensity [dB]')
    plt.title(f'Spectrogram Snippet {i // snippet_samples + 1}')
    plt.tight_layout()
    
    # Save the spectrogram as an image
    output_file = os.path.join(output_dir, f'spectrogram_snippet_{i // snippet_samples + 1}.png')
    plt.savefig(output_file)
    plt.close()
    
    print(f"Saved {output_file}")

print("All spectrogram snippets with jamming levels saved.")

Make sure you have the required Python packages installed:

pip install numpy matplotlib scipy