Parametric Precoding Based on Improved Dynamic Gradient Descent in Multibeam Satellite Communications

Jiayu Wang, Rugui Yao, Donghui Xu, Ye Fan, Xiaoya Zuo
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Abstract

Precoding and beamforming have been studied in multibeam satellite. In this paper, we propose a precoding method based on dynamic gradient descent, which is suitable for large array antenna and multiuser multibeam satellite environment. This method doesn't need complex vector or matrix design because of combining zero-forcing and maximum ratio transmission. And gradient descent algorithm is used to solve this combining zero-forcing and maximum ratio transmission model. Meanwhile, the convergence of gradient descent is also proved. The simulation results show that the improved gradient descent based on parametric design can get higher sum rate, whether it is in the case of multiple users with massive antennas or small users with a few number of antennas. Meanwhile, for the gradient descent convergence problem, we propose a dynamic adaptive learning rate updating method, which has faster and better convergence performance than traditional gradient descent algorithm.
基于改进动态梯度下降的多波束卫星通信参数预编码
对多波束卫星的预编码和波束形成进行了研究。本文提出了一种基于动态梯度下降的预编码方法,该方法适用于大型阵列天线和多用户多波束卫星环境。该方法结合了零强迫和最大传动比传动,不需要复杂的矢量或矩阵设计。采用梯度下降算法求解该零强迫与最大传动比相结合的传动模型。同时,还证明了梯度下降算法的收敛性。仿真结果表明,无论是多用户多天线还是小用户少天线情况下,基于参数化设计的改进梯度下降算法都能获得较高的和率。同时,针对梯度下降算法的收敛性问题,提出了一种动态自适应学习率更新方法,该方法具有比传统梯度下降算法更快更好的收敛性能。
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