Exploration of the application of optimisation algorithm using stochastic gradient descent method in satellite resource allocation

被引:0
|
作者
Zhao D. [1 ,2 ]
Xiong W. [1 ]
Shi J. [3 ]
机构
[1] Science and Technology on Complex Electronic System Simulation Laboratory, University of Aerospace Engineering, Beijing
[2] Dfh Satellite CO. Ltd, Beijing
[3] North Automatic Control Technology Institute, Shanxi, Taiyuan
关键词
Beam assignment; Performance test; Satellite resource allocation; Simulation experiment; Stochastic gradient descent method;
D O I
10.2478/amns-2024-1527
中图分类号
学科分类号
摘要
With the popularization and development of communication technology, the resource allocation problem of satellites has become a hot research topic. This study proposes a model for satellite resource allocation through the development of a beam mobilization system model and problem modeling. Then, on the basis of the linear stochastic gradient descent method, the classification accuracy of the algorithm is improved by adjusting the algorithm-solving method. Then its weight assignment method is improved to get the improved weighted linear stochastic gradient descent method. Using the optimized weighted linear stochastic gradient descent method to solve the satellite resource allocation problem from the perspective of the original problem, a model based on IWLSGD is designed and tested for performance. Through simulation experiments, the beam allocation service value of the satellite resource allocation model in this paper is 193, which is 4.32% and 3.21% higher than that of LSGD and WLSGD, respectively, and iterative convergence is faster, and its operation time and service value performs the best under different numbers of communication time slots. The system revenue, system access success rate, and system satisfaction under the interference environment between LEO and GEO are maintained at 15208, 0.8~1.0, and 85%, and keep around 7500, 1, and 75% under 5G base station interference. The satellite resource allocation model in this paper can effectively improve the utilization efficiency of communication resources and better adapt to dynamically changing interference scenarios. © 2024 Demin Zhao et al., published by Sciendo.
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