MATLAB Implementation of QAM Modulation and Demodulation

This MATLAB implementation demonstrates Quadrature Amplitude Modulation (QAM) and demodulation techniques for data transmission. QAM modulation is a widely used digital modulation scheme that enables higher data rates within limited bandwidth by varying both amplitude and phase of the carrier signal. The demodulation process reconstructs original data from the modulated signal using constellation point detection and decision-making algorithms. The implementation includes comprehensive channel modeling with Rayleigh fading to simulate multipath propagation effects in wireless environments, where signal components arrive via multiple paths with different delays and amplitudes. Additive White Gaussian Noise (AWGN) is incorporated to represent background noise that affects signal quality and bit error rate performance. Key MATLAB functions utilized in this implementation include: - qammod() and qamdemod() for modulation and demodulation operations - rayleighchan() for creating Rayleigh fading channel object - awgn() for adding white Gaussian noise to the signal - berawgn() for theoretical bit error rate calculations - scatterplot() for constellation diagram visualization The code structure involves generating random data symbols, mapping them to QAM constellation points, applying channel effects through convolution with Rayleigh channel coefficients, adding noise with specified SNR levels, and performing demodulation with maximum likelihood detection. Performance evaluation includes calculating bit error rates (BER) across different SNR values and comparing with theoretical results to validate implementation accuracy. This implementation provides practical insights into QAM system performance under realistic wireless channel conditions, serving as an educational tool for understanding digital communication systems and as a foundation for more advanced communication system simulations.