commlab 0.3.0

Communication Lab utilities for signal processing and noise addition

CommLab - Communication Laboratory Utilities

A Python package providing utility functions for communication systems experiments and simulations.

Features

• AWGN Noise Addition: Add Additive White Gaussian Noise to signals with specified SNR
• Supports both real and complex-valued signals
• Works with multi-dimensional arrays
• Easy to use and extend

Installation

From source (Development mode)

1. Clone or download this repository
2. Navigate to the package directory
3. Install in editable mode:

pip install -e .

This allows you to modify the source code and see changes immediately without reinstalling.

Usage

Basic Example

import numpy as np
from commlab import awgn

# Create a simple BPSK signal
signal = np.array([1, -1, 1, -1, 1, -1])

# Add AWGN with SNR = 10 dB
noisy_signal = awgn(signal, SNRdb=10)

QPSK Example

import numpy as np
from commlab import awgn

# Create QPSK symbols
qpsk_symbols = np.array([1+1j, -1+1j, -1-1j, 1-1j]) / np.sqrt(2)

# Add noise with 15 dB SNR
noisy_qpsk = awgn(qpsk_symbols, SNRdb=15)

With Oversampling

import numpy as np
from commlab import awgn

# Oversampled signal (4 samples per symbol)
oversampled_signal = np.repeat([1, -1, 1, -1], 4)

# Add noise (L=4 for 4 samples per symbol)
noisy_signal = awgn(oversampled_signal, SNRdb=10, L=4)

Function Reference

awgn(s, SNRdb, L=1)

Add Additive White Gaussian Noise to a signal.

Parameters:

• s (array_like): Input signal (real or complex)
• SNRdb (float): Signal-to-Noise Ratio in dB
• L (int, optional): Samples per symbol (default=1)

Returns:

• r (ndarray): Noisy signal

Requirements

• Python >= 3.7
• NumPy >= 1.20.0

Future Extensions

This package is designed to be easily extensible. Future versions may include:

• Modulation schemes (BPSK, QPSK, QAM)
• Demodulation functions
• BER calculation utilities
• Eye diagram plotting
• Channel models

License

MIT License

Contributing

Feel free to add more functions as needed for your communication lab experiments!