| 引用本文： |
-
张迎希,姜大鹏,邵丰伟,等.基于多目标元启发式算法的低轨卫星波束调度优化方法[J].电讯技术，2026，66（5）： - . [点击复制]
- ZHANG Yingxi,JIANG Dapeng,SHAO Fengfei,et al.An Optimized Beam Scheduling Method for Low Earth Orbit Satellite Based on Multi-object Metaheuristic Optimization Algorithm[J].，2026，66（5）： - . [点击复制]
|
|
| 摘要: |
| 在通信业务量需求高度非均匀分布的场景中，通过应用高效的动态波束调度方法，可以有效提高低轨通信卫星的系统容量。基于现有低轨卫星星载相控阵多波束天线架构，通过确定优化变量以及问题的约束条件，建立了低轨卫星波束调度的优化问题模型，并对该优化问题进行了计算复杂度分析，验证了该问题的NP-难性质。为了解决问题的NP-难性质，同时为实际卫星波束调度业务场景提供更多样化的选择，利用基于遗传算法原理的改进非支配遗传算法(Non-dominated Sorting Genetic Algorithms-Ⅱ，NSGA-Ⅱ)以及改进强度帕累托进化算法(Strength Pareto Evolutionary Algorithm 2，SPEA2)以覆盖更多的通信终端并减少波束间干扰的波束调度优化方法。在数值仿真结果中，NSGA-Ⅱ和SPEA2输出的近似帕累托解分别为19个和25个；而在代表近似最优方案的拐点解的性能对比上，NSGA-Ⅱ和SPEA2在干扰规避指标上仅有8%的差别，但NSGA-Ⅱ拐点解的覆盖业务量指标则超过SPEA2拐点解30%。 |
| 关键词: 卫星通信 多波束卫星系统 波束调度 启发式优化 多目标优化 |
| DOI：10.20079/j.issn.1001-893x.241219002 |
|
| 基金项目:国家自然科学基金资助项目（62371287；62001291）；上海市"科技创新行动计划"高新技术领域项目（20511106605） |
|
| An Optimized Beam Scheduling Method for Low Earth Orbit Satellite Based on Multi-object Metaheuristic Optimization Algorithm |
| ZHANG Yingxi,JIANG Dapeng,SHAO Fengfei,WU Tong,GENG Junping,JIN Ronghong,CHEN Jingfeng |
| (1.Department of Electronic Engineering，Shanghai Jiao Tong University，Shanghai 200240，China;2.China Ship Development and Design Center，Wuhan 430064，China;3.Shanghai Spacecom Satellite Technology Ltd.，Shanghai 200240，China) |
| Abstract: |
| In scenarios where communication traffic demand is highly unevenly distributed，the application of efficient dynamic beam scheduling methods can significantly enhance the system capacity of low Earth orbit(LEO) communication satellites.Based on the existing onboard phased array multi-beam antenna architecture of LEO satellites，an optimization problem model for LEO satellite beam scheduling problem is provided by formulating the optimization variables and constrained conditions.The computational complexity analysis of this optimization problem confirms its NP-hard essence.To address the NP-hardness of the problem and provide a more diverse set of options for actual satellite beam scheduling scenarios，Non-dominated Sorting Genetic Algorithms-Ⅱ(NSGA-II) and Strength Pareto Evolutionary Algorithm 2(SPEA2)，which are based on principles of genetic algorithm，are utilized to optimize beam scheduling results aiming to covers more communication terminals while reducing inter-beam interference.In the numerical simulation results，the approximate Pareto solutions calculated by NSGA-Ⅱ and SPEA2 are 19 and 25 respectively.In terms of the performance comparison of the corner solution，there is only an 8% difference between NSGA-Ⅱ and SPEA2 in the interference avoidance specification，but the coverage traffic specification of NSGA-Ⅱ exceeds that of SPEA2 by 30%. |
| Key words: satellite communication multi-beam satellite system beam scheduling metaheuristic optimization multi-object optimization |
《电讯技术》编辑部 