Performance Difference Analysis of LDPC Codes, Turbo Codes, and Convolutional Codes in Deep Space Communication

With the continuous advancement of human space exploration activities, the communication distance continues to extend, which puts forward more stringent requirements for communication technology's dependability and transmission effectiveness. This research examines the efficacy of Low-Density Parity-Check (LDPC) codes, Turbo, and convolutional codes in the presence of additive white Gaussian noise (AWGN) inside deep space communication. The reliability of these coding schemes in high-noise environments is evaluated by comparing their bit error rate (BER) and frame error rate (FER) at varying Signal to Noise Ratio (SNR) levels. Results show that while all codes exhibit high BER and FER at low-to-moderate SNR, LDPC codes outperform others at high SNR, nearing the theoretical limit. Turbo codes also demonstrate strong performance, whereas convolutional codes offer limited improvement. These findings highlight LDPC codes as the optimal choice for deep space communication due to their robust error correction capability in extreme noise conditions. Their near-Shannon-limit performance sets a benchmark for future coding research, particularly in developing next-generation communication systems for ultra-long-distance space missions with stringent power and bandwidth constraints.