Convolutional Encoding and Viterbi Decoding Implementation

Implementation of convolutional encoding and Viterbi algorithm decoding, followed by plotting Signal-to-Noise Ratio (SNR) versus Bit Error Rate (BER) curves to comprehensively demonstrate the performance results. The implementation includes generating convolutional codes using polynomial generators, typically implemented with shift registers and XOR operations. The Viterbi decoder employs dynamic programming principles for maximum likelihood sequence estimation, utilizing path metric calculations and traceback operations. The BER performance analysis involves adding AWGN to the encoded signal and comparing decoded bits with original data across various SNR values. Key implementation aspects include constraint length handling, branch metric computation, and survivor path management in the Viterbi algorithm. The plotting functionality uses numerical computing libraries to generate quantitative performance analysis charts, demonstrating the error correction capability of the convolutional coding system under different noise conditions.