Basic Digital Communication System

In this experiment, we implement a basic digital communication system using MATLAB simulation software, as illustrated in Figure 1. The implementation begins with generating random binary signals with equal probability distribution of 0s and 1s using MATLAB's random number generation functions. These bits are then mapped to 16QAM constellation points through digital modulation, where the signal is decomposed into in-phase (real) and quadrature (imaginary) components for independent processing. Both signal components undergo pulse shaping using root-raised-cosine (RRC) filters, implemented through MATLAB's digital filter functions with specified roll-off factors. The system then introduces additive white Gaussian noise (AWGN) to simulate channel impairments, using MATLAB's awgn function with configurable signal-to-noise ratio (SNR) parameters. The noisy signals pass through matched RRC filters (optimal receivers for pulse-shaped signals) for signal detection enhancement. The processing continues with sampling at optimal instants using symbol timing recovery algorithms, followed by decision-making through constellation point demapping and threshold detection. Finally, the detected bits are compared with the original transmitted sequence using MATLAB's error calculation functions to determine the bit error rate (BER), providing performance evaluation for the 16QAM digital communication system under various noise conditions.