MATLAB Simulation and Analysis of Digital Baseband Transmission Systems

Digital baseband transmission systems serve as fundamental components in modern communication systems, where MATLAB simulations enable intuitive performance analysis. Eye diagrams and inter-symbol interference (ISI) represent critical metrics for evaluating system quality. Simulation of digital baseband transmission systems typically involves several key steps implemented through MATLAB code. The process begins with generating a random binary sequence using functions like randi() or rand() for input signal creation. Subsequent pulse shaping employs raised-cosine filters implemented via the rcosdesign() function, which controls roll-off factors to manage bandwidth and ISI. The shaped signal then passes through an additive white Gaussian noise (AWGN) channel simulated using awgn() function with adjustable SNR parameters. At the receiver end, matched filtering (typically using the same filter as transmission) followed by sampling and threshold detection completes the demodulation process. Eye diagram analysis provides essential insights into system performance. The eye diagram's opening degree indicates the system's resilience to noise and ISI, where a wide-open "eye" corresponds to ideal performance. Practical implementations use MATLAB's eyediagram() function to visualize signal quality, with parameter adjustments revealing how noise and distortion cause eye closure. Code implementation involves plotting synchronized signal segments over two symbol periods using comm.EyeDiagram System object or similar tools from the Communications Toolbox. Inter-symbol interference significantly impacts system performance, primarily caused by bandwidth limitations and multipath effects. MATLAB simulations demonstrate how ISI causes current symbol decisions to be influenced by adjacent symbols. The impact can be quantified through bit error rate (BER) calculations using biterr() function and controlled by adjusting roll-off factors in pulse-shaping filters. The comm module offers pre-built System objects for constructing end-to-end communication models, while parametric studies involving roll-off coefficients and SNR values provide design guidance for practical implementations through systematic performance comparisons.