A Python-based GUI application for simulating digital and analog modulation techniques with real-time signal analysis.

This project provides a comprehensive tool for simulating various modulation techniques and analyzing their signal characteristics. It features:

• Digital Modulation: FSK, PSK, ASK
• Analog Modulation: AM, FM
• Signal Analysis: Bandwidth, SNR, Spectral Efficiency
• AES Encryption: Secure data transmission simulation
• Audio Playback: Listen to generated signals
• Export Options: Save signals as WAV or plots as PNG/PDF

Built with tkinter for the GUI and matplotlib for visualization.

• FSK/PSK/ASK: Digital modulation with configurable carrier frequencies
• AM/FM: Analog modulation with customizable parameters

• Bandwidth Calculation: FFT-based spectral analysis
• SNR Estimation: Signal-to-noise ratio metrics
• Transmission Distance: Path loss model for range estimation

• AES-128 Encryption: Secure text input before modulation

• Save signals as .wav files
• Export plots to /JPEG/PNG/PDF
• Real-time audio playback

Clone the repository:

git clone https://github.com/armanghobadi/wavelab.git
cd modulation-simulator

Install dependencies:

pip install -r requirements.txt

Run the application:

python app.py

• Python 3.8+
• Required libraries:

numpy, matplotlib, scipy, sounddevice, ttkthemes, pycryptodome

• Input text/message
• Bit rate, carrier frequency, sampling rate
• Duration and amplitude

• Digital: FSK/PSK/ASK
• Analog: AM/FM
• Bit-1 frequency (for FSK)

• Toggle AES-128 encryption
• 16-byte key input

• View bandwidth, SNR, and spectral efficiency
• Estimate transmission distance

1. Enter text (e.g., Hello).
2. Select FSK modulation with:
   • Carrier = 600 Hz, Bit-1 Frequency = 1200 Hz
3. Enable AES Encryption (optional).
4. Click Generate Signal → View plots.
5. Click Analyze → Check SNR/Bandwidth.
6. Play Audio or Save as WAV.

This project is licensed under the MIT License. See the LICENSE file for details.

• Telecommunications education
• Signal processing prototyping
• Encryption-integrated modulation testing

Made with ❤️ for the signal processing community!