MAP Algorithm - Maximum A Posteriori Probability Implementation
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Resource Overview
This MATLAB program implements the Maximum A Posteriori (MAP) algorithm with comprehensive communication system components including convolutional encoding/decoding, BPSK modulation, and AWGN channel simulation. The code also generates performance analysis through Bit Error Rate (BER) versus Signal-to-Noise Ratio (SNR) plots.
Detailed Documentation
This MATLAB implementation provides a complete Maximum A Posteriori (MAP) probability algorithm framework. The program features convolutional encoding using generator polynomials and corresponding MAP-based decoding with forward-backward probability calculations. It incorporates BPSK modulation for symbol mapping and AWGN channel simulation using randn function for noise generation. The code includes performance metrics calculation that plots BER versus SNR curves through Monte Carlo simulations, enabling quantitative analysis of communication system performance under varying channel conditions. This integrated implementation serves as a valuable tool for researchers and engineers in signal processing and communications, facilitating convenient performance evaluation across different parameter configurations through modular function design and systematic simulation loops.
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