Implementation of Convolutional Codes over AWGN Channels

The implementation of convolutional codes over Additive White Gaussian Noise (AWGN) channels is critically important in communication systems. This implementation utilizes both Simulink model files and MATLAB .m files to simulate the complete communication chain, including encoding, AWGN channel transmission, and Viterbi decoding. Convolutional coding represents a fundamental channel coding technique that enhances signal reliability and reduces bit error rates through its error correction capabilities. The implementation typically involves configuring parameters such as constraint length, code rate, and generator polynomials, while the Viterbi algorithm decodes the received sequence using trellis-based maximum likelihood sequence estimation. Understanding these implementation methods is essential for designing and optimizing robust communication systems, particularly when evaluating performance metrics like Bit Error Rate (BER) versus Signal-to-Noise Ratio (SNR) characteristics.