Gaussian White Noise Algorithm Implementation

Below is the source code implementation of the Gaussian white noise algorithm, designed for MATLAB programming in communication system applications. This algorithm serves to simulate noise signals in communication systems, where noise represents an unavoidable factor affecting system performance. By modeling and analyzing noise characteristics, engineers and researchers can better understand and enhance communication system robustness.

The MATLAB implementation employs the randn() function to generate normally distributed random numbers with zero mean and unit variance, which forms the basis of Gaussian white noise. Users can scale the noise power by adjusting the standard deviation parameter according to specific signal-to-noise ratio (SNR) requirements. The algorithm includes features for noise signal generation, power normalization, and integration with communication signals.

This source code provides a practical tool for noise analysis and processing in MATLAB environments, enabling deeper understanding of Gaussian white noise characteristics, statistical properties, and its impact on communication system performance. The implementation follows standard signal processing techniques and can be easily adapted for various communication scenarios including wireless systems, digital modulation schemes, and channel capacity studies.