QPSK System with Convolutional Coding Implementation

In this article, we provide a comprehensive description of code implementation for a QPSK system employing convolutional coding. We demonstrate how to evaluate system performance through code execution, featuring convolutional encoder/decoder implementations integrated with QPSK modulator/demodulator components. The code incorporates trellis-based decoding algorithms (e.g., Viterbi algorithm) for error correction and includes SNR-varying BER performance analysis. Key functions include: - Convolutional encoding with polynomial generator configuration - QPSK modulation/demodulation with constellation mapping - AWGN channel simulation with variable SNR settings - Bit error rate calculation through Monte Carlo simulation Through executed code examples, users can observe BER performance across different signal-to-noise ratios and analyze system characteristics. Detailed code annotations explain functionality and implementation approaches, including trade-offs between coding gain and computational complexity. The provided code and explanations enable readers to deeply understand both theoretical principles and practical implementation of convolutionally-coded QPSK systems, with modular structure allowing customization of code parameters and performance metrics.