Gauss_generator: Parameter-Based Deterministic Real Gaussian Process Generation

This document describes Gauss_generator.m, which implements parameter-driven deterministic real Gaussian process generation using specified Doppler shifts, coefficients, and phase shifts. The gaussian.m program algorithmically computes discrete Doppler frequency shifts, weighting coefficients, and phase offsets for precise waveform control. Rice_generator.m extends Rayleigh process modeling by integrating line-of-sight components to simulate Rice fading channels. Suzuki_generator.m combines log-normal and Rayleigh distributions to produce deterministic Suzuki processes for composite fading scenarios. The toolkit includes supplementary modules: Rayleigh_Doppler_multiPath.m (multipath Rayleigh Doppler simulation), Rayleigh_Doppler_singlePath.m (single-path Rayleigh Doppler modeling), rayleigh_Filter_Model.m (filter-based Rayleigh process generation), pdf_cdf_gen.m (probability density and cumulative distribution function computation), test_rayleigh_pdf.m (Rayleigh distribution verification), and rayleigh.m (core Rayleigh process implementation). Each module employs specialized algorithms for wireless channel emulation, including inverse Fourier transforms for Doppler spectrum shaping and statistical methods for fading characteristic accuracy.