ERA-LEO: An Efficient Rate Adaptation with Probabilistic Constellation Shaping for LEO Satellite Networks

With the increasing deployment of Low Earth Orbit (LEO) satellites (e.g., Starlink), rate adaptation has been widely applied in satellite communication systems to rapidly adapt changing satellite-ground channel. However, the state-of-the-art rate adaptation solutions still do not approach the Shannon capacity, since they always operates in discrete steps (e.g., switching between fixed modulation orders and coding rates), leading to abrupt performance deterioration when the channel fluctuates between two thresholds. We propose a new plug-and-play rate adaptation, called ERA-LEO integrated to satellite communication systems without any extra hardware modification. For adapting smoothly to changes in channels, we first design a probabilistic constellation shaping enabled system to provide a continuous and more granular adjustment of the constellation by tuning the probability distribution of symbols. Second, to avoid the frequent feedback, used to select a target probability distribution based on the channel condition, we establish a theoretical model to demonstrate that the SNR of the return link can reliably predict that of the forward link, and present a lightweight prediction mechanism based on neural network. We also implement ERA-LEO prototype using FPGA-based software defined radio platforms. The extensive evaluations demonstrate ERA-LEO achieves an average gain of 2.19 dB compared to state-of-the-art baselines and a 43.08% improvement in network throughput.