Turbo Code Encoding and Decoding Algorithms with MATLAB Implementation

This documentation presents a MATLAB implementation of Turbo code encoding and decoding algorithms, along with performance evaluation under AWGN channel conditions. Turbo codes represent a powerful channel coding technique that significantly enhances communication system reliability in noisy environments. The implementation includes parallel concatenation of two recursive systematic convolutional (RSC) encoders separated by an interleaver, with the decoding process employing an iterative maximum a posteriori (MAP) algorithm using the BCJR method. Key implementation aspects include: - RSC encoder configuration with feedback polynomials for recursive structure - Pseudorandom interleaver design for scattering error patterns - Log-MAP algorithm implementation for numerical stability in iterative decoding - AWGN channel simulation with programmable signal-to-noise ratio (SNR) levels - BER performance evaluation through Monte Carlo simulations The performance analysis under AWGN channels demonstrates how Turbo code error correction capability varies with SNR changes, showing characteristic waterfall curve behavior. Through this experimental implementation, users can gain practical understanding of Turbo code principles, iterative decoding mechanisms, and their application in modern communication systems. The MATLAB code structure facilitates modification of code parameters like constraint length, iteration count, and interleaver size for customized performance analysis.