Bit Error Rate Comparison with and without Channel Coding Technology

In the original implementation, we expanded the text length while preserving key concepts using the following methodology: This program employs 16QAM modulation to process a binary source sequence. The 16QAM technique divides signals into 16 distinct phase and amplitude combinations, enabling higher information transmission within limited bandwidth. Code implementation typically involves mapping 4-bit symbols to 16 constellation points using quadrant-based amplitude scaling. We implemented (7,4) cyclic code for channel encoding. This coding scheme can correct a specific number of transmission errors, enhancing signal reliability. The algorithm utilizes polynomial division over GF(2) for encoding, where 4 information bits are extended to 7 coded bits with error correction capability. For baseband modulation, we applied a raised-cosine roll-off filter. This filter optimally shapes the signal spectrum to minimize intersymbol interference (ISI) during transmission. The implementation involves convolving the digital signal with a raised-cosine impulse response function parameterized by the roll-off factor. To simulate realistic channel conditions, we added Gaussian white noise to the transmitted signal. This additive noise interferes with the signal and increases bit error probability. The simulation typically generates AWGN using random number generators with specified signal-to-noise ratio (SNR) values. We used matched filtering for demodulation and plotted the resulting constellation diagrams. The matched filter maximizes SNR by correlating the received signal with the known pulse shape. Constellation visualization helps analyze signal distortion and noise impact during transmission. For signal decoding, we implemented minimum Euclidean distance decoding decision. This method effectively recovers original signals by calculating geometric distances between received points and constellation points, selecting the closest valid symbol to minimize bit errors. Finally, we generated comparative bit error rate graphs for systems with and without channel coding technology. By analyzing these plots, we can evaluate how channel coding improves transmission performance under various noise conditions. The BER curves are typically plotted against Eb/N0 ratios to demonstrate coding gain. Through these enhancements, we maintained the original key concepts while adding detailed technical explanations and implementation considerations, making the content more comprehensive and clearer for technical audiences.