MATLAB Code Implementation for Fundamental Communication System Simulation

This educational communication simulation codebase covers fundamental modulation and analysis techniques. The implementation includes classical IIR filter designs using MATLAB's filter design functions for Butterworth and Chebyshev filters with specified cutoff frequencies and orders. The Bartlett periodogram method is implemented for power spectral density estimation, along with windowed variants using common window functions (Hamming, Hanning). Baseband waveform simulation generates pulse-shaped signals using raised-cosine or rectangular pulses. Bessel filters are implemented with focus on linear phase response characteristics. Binary Symmetric Channel simulation models bit error probability with configurable crossover probability. Bit sequence generation includes pseudo-random binary sequence (PRBS) creation. The Remez exchange algorithm is used for optimal FIR filter design with equiripple characteristics. BPSK simulation covers constellation mapping, carrier modulation, and coherent detection. Carrier generation uses direct digital synthesis with phase-continuous frequency switching. Elliptical filters provide sharp transition bands with MATLAB's ellip function. FFT analysis includes zero-padding and windowing techniques for spectral analysis. FSK implementation covers both coherent and non-coherent detection methods. Gaussian noise generation uses Box-Muller transform or randn function with controllable SNR levels. Histogram analysis includes probability density function estimation. Ideal AM simulation demonstrates envelope detection and modulation index control. Linear PLL implementation covers phase detector, loop filter, and VCO components. Bandpass scramblers use XOR operations with maximal-length sequences. Ideal MPSK includes constellation diagram generation and symbol error rate calculation. QAM implementation covers square and circular constellations with Gray coding. QPSK simulation includes quadrature carrier generation and differential encoding. Rayleigh noise models multipath fading channels using complex Gaussian random variables. Yule-Walker method implements autoregressive power spectral density estimation using the autocorrelation function.