Space communications feature large round-trip time delays (for example, between 6.5 and 44 minutes for Mars to Earth and return, depending on the actual distance between the two planets) and highly variable data error rates, for example, bit error rate (BER) of 10−5 is very comand even higher BERs on the order of 10−1 is observed in the deep- space environment. We develop a new content transfer protocol based on RaptorQ codes and turbo codes together with a real-time channel prediction model to maximize file transfer from space vehicles to the Earth stations. While turbo codes are used to correct channel errors, RaptorQ codes are applied to eliminate the need for negative-acknowledgment of the loss of any specific packet. To reduce the effect of channel variation, we develop a practical signal-to-noise ratio (SNR) prediction model that is used to periodically adjust the turbo encoder in distant source spacecraft. This new protocol, termed as dynamic code selection method (DCSM), is compared with two other methods: turbo based genie method (upper bound of DCSM performance) assuming that the channel condition is perfectly known in advance and a static method in which a fixed turbo encoder is used throughout a communication pass. Simulation results demonstrate that the genie can increase telemetry channel throughput expressed in terms of the total number of successfully delivered files during a communication pass by about 20.3 % and DCSM achieves more than 99 % of genie, compared to the static approach being used currently
