基于改进遗传算法的低轨通信卫星跳波束调度策略

doi:10.7523/j.ucas.2023.054

中国科学院大学学报 ›› 2025, Vol. 42 ›› Issue (3): 382-391.DOI: 10.7523/j.ucas.2023.054

• 电子信息与计算机科学 • 上一篇

基于改进遗传算法的低轨通信卫星跳波束调度策略

张盼盼^1,2, 常家超³, 邹诚^1,2, 李国通^1,3,4

1 中国科学院微小卫星创新研究院, 上海 201304;
2 中国科学院大学, 北京 100049;
3 上海垣信卫星科技有限公司, 上海 201600;
4 上海科技大学, 上海 201210

收稿日期:2023-02-22 修回日期:2023-05-12 发布日期:2023-05-12
通讯作者: 李国通,E-mail:ligt@microsate.com
基金资助:
国家高层次人才特殊支持计划(WRJH19DH01)和上海市青年科技英才扬帆计划(19YF1446400)资助

Beam hopping scheduling strategy of LEO communication satellite based on improved genetic algorithm

ZHANG Panpan^1,2, CHANG Jiachao³, ZOU Cheng^1,2, LI Guotong^1,3,4

1 Innovation Academy for Microsatellites, Chinese Academy of Sciences, Shanghai 201304, China;
2 University of Chinese Academy of Sciences, Beijing 100049, China;
3 Shanghai Yuanxin Satellite Technology Co., Ltd, Shanghai 201600, China;
4 ShanghaiTech University, Shanghai 201210, China

Received:2023-02-22 Revised:2023-05-12 Published:2023-05-12

摘要/Abstract

摘要： 低轨通信卫星可以突破地形限制，与6G共同搭建天地一体化信息网络。由于其面对的全球用户需求分布不均，针对卫星关于地面固定终端的波束调度问题，提出一种能够实现时延和干扰双重优化的波束调度策略。结合发射功率、载噪比等约束，建立以排队时延和同频干扰最小化为优化目标的模型。通过分步优化，设计了需求分簇、时隙分配和波位匹配的波束跳变方案。其中针对波位匹配过程中的干扰优化问题，提出基于遗传算法的“簇内波位自交叉”的染色体交叉机制。仿真结果表明，与其他算法相比，改进遗传算法的同频干扰降低约32%~58%，且所提策略能够在资源分配周期内完成波束调度，同时实现时延和干扰的双重优化。

关键词: 低轨卫星, 跳波束, 调度策略, 遗传算法

Abstract: Low earth orbit (LEO) communication satellites can break through terrain constraints and work with 6G to build an integrated space-ground information network. In terms of the beam scheduling problem of satellites for fixed terminals on the ground, a beam scheduling strategy that can achieve dual optimization of interference and delay is proposed, considering that the uneven distribution of global user demands exists. The model with the optimization goal of minimizing the queuing delay and co-channel interference is constructed, combining with constraints such as transmit power as well as carrier-to-noise ratio. By means of step-by-step optimization, a beam-hopping scheme including demand clustering, time slot allocation and beam position matching is designed. When it comes to the interference optimization problem in the beam position matching process, a genetic algorithm-based chromosome crossover mechanism of “beam position self-crossover within a cluster” is proposed. The simulation results show that the improved genetic algorithm can reduce the co-channel interference by 32% to 58% compared with the other algorithms. Besides, the proposed strategy can schedule the beam within the resource allocation period while achieving dual optimization of delay and interference.

Key words: LEO satellite, beam-hopping, scheduling strategy, genetic algorithm

中图分类号:

TN927+.23

张盼盼, 常家超, 邹诚, 李国通. 基于改进遗传算法的低轨通信卫星跳波束调度策略[J]. 中国科学院大学学报, 2025, 42(3): 382-391.

ZHANG Panpan, CHANG Jiachao, ZOU Cheng, LI Guotong. Beam hopping scheduling strategy of LEO communication satellite based on improved genetic algorithm[J]. Journal of University of Chinese Academy of Sciences, 2025, 42(3): 382-391.

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基于改进遗传算法的低轨通信卫星跳波束调度策略

Beam hopping scheduling strategy of LEO communication satellite based on improved genetic algorithm

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