基于Online-GRU信道预测的星上自适应功率控制方法

Satellite adaptive power control method based on Online-GRU channel prediction

摘要:

针对传统卫星功率控制方法存在资源浪费、时延长的问题，提出一种基于在线-门控循环单元(Online-GRU)信道预测的星上自适应功率控制方法，通过在线训练更新网络参数来解决离线预测算法存在的累积误差的问题。仿真结果表明，提出的在线训练算法比离线算法预测精确度提升了38.30%，相比在线-长短期记忆网络(Online-LSTM)节约了63.21%的训练时间；提出的自适应功率控制方法比固定发射功率的方法节约了55.74%的发射功率；同时，相比基于地面定时反馈信道状态的自适应功率控制方法具备更好的鲁棒性。

Abstract:

In response to the problems of resource waste and long propagation time delay in traditional satellite power control methods, this paper proposes a satellite adaptive power control method based on Online Gate Recurrent Unit(Online-GRU) channel prediction, which solves the cumulative error of offline prediction algorithms by updating network parameters through online training. The simulation results show that the proposed online training algorithm improves the prediction accuracy by 38.30% compared to offline algorithms, saves 63.21% of training time compared to Online Long Short Term Memory(Online-LSTM), and saves 55.74% of transmission power compared to the fixed transmission power method. At the same time, the proposed adaptive power control method has better robustness compared to the adaptive power control method based on ground timing feedback channel state.