基于改进SA-NSGAⅡ的多波束卫星动态资源分配方法

doi:10.12305/j.issn.1001-506X.2024.12.31

系统工程与电子技术 ›› 2024, Vol. 46 ›› Issue (12): 4222-4230.doi: 10.12305/j.issn.1001-506X.2024.12.31

• 通信与网络 • 上一篇

基于改进SA-NSGAⅡ的多波束卫星动态资源分配方法

饶悦¹, 杨健²^,³, 孙国敏¹^,*, 张伟¹^,⁴, 邵怀宗¹^,³, 林静然¹

1. 电子科技大学信息与通信工程学院, 四川成都 611731
2. 北京理工大学网络空间安全学院, 北京 100081
3. 电磁空间认知与智能控制技术实验室, 北京 100089
4. 电子信息控制重点实验室, 四川成都 610036

收稿日期:2023-10-11 出版日期:2024-11-25 发布日期:2024-12-30
通讯作者: 孙国敏
作者简介:饶悦(2001—), 男, 硕士研究生, 主要研究方向为卫星通信
杨健(1982—), 男, 研究员, 博士, 主要研究方向为群体电磁博弈
孙国敏(1989—), 女, 助理研究员, 博士, 主要研究方向为辐射源智能识别、卫星通信
张伟(1985—), 男, 高级工程师, 博士, 主要研究方向为非合作信号与信息处理、电子对抗
邵怀宗(1967—), 男, 教授, 博士, 主要研究方向为无线通信、电子对抗
林静然(1978—), 男, 教授, 博士, 主要研究方向为无线通信信号处理与优化
基金资助:
国家自然科学基金(U20B2070)

Multi-beam satellite dynamic resource allocation method based on improved SA-NSGAⅡ

Yue RAO¹, Jian YANG²^,³, Guomin SUN¹^,*, Wei ZHANG¹^,⁴, Huaizong SHAO¹^,³, Jingran LIN¹

1. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
2. School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China
3. Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology, Beijing 100089, China
4. Key Laboratory of Science and Technology on Electronic Information Control, Chengdu 610036, China

Received:2023-10-11 Online:2024-11-25 Published:2024-12-30
Contact: Guomin SUN

摘要/Abstract

摘要：

多波束卫星作为地球静止轨道卫星移动通信的重要手段，能够实现远距离数据传输与通信交流。为了满足多样化的用户需求，需要考虑不同用户间的通信速率、频谱利用效率以及信道缓存等问题，这给卫星通信的动态资源分配带来巨大的挑战。就多波束卫星缓存限制下的用户满意度和频谱效率优化问题，提出一种基于可行域边界投影的模拟退火-带精英策略的非支配排序遗传算法Ⅱ(simulated annealing-elitist non-dominated sorting genetic algorithm, SA-NSGA Ⅱ)。所提算法采用投影法将可行域外的迭代点投影到可行边界，实现历史优化信息的有效保留，进而提高非支配排序遗传算法(non-dominated sorting genetic algorithm，NSGA Ⅱ)的优化效率。仿真实验结果表明，所提算法不仅能够将用户缓存控制在规定门限内，还能有效提高用户满意度和优化频谱效率。

关键词: 多波束卫星通信, 用户满意度, 频谱效率, 信道缓存, 模拟退火-带精英策略的非支配排序遗传算法

Abstract:

As an important means of mobile communication of geostationary orbit satellites, multi-beam satellite can realize long-distance data transmission and telecommunication. In order to meet the diverse needs of users, it is necessary to consider the communication rates among different users, spectrum utilization efficiency and channel caching, which brings great challenges to the dynamic resource allocation of satellite communication. A simulated annealing-elitist non-dominated sorting genetic algorithm (SA-NSGA Ⅱ) based on feasible region boundary projection is proposed for the optimization of user satisfaction and spectrum efficiency with the limitation of multi-beam satellite cache. The proposed algorithm uses projection method to project the iteration points outside the feasible region to the feasible boundary to realize the effective retention of historical optimization information and to improve the optimization efficiency of non-dominated sorting genetic algorithm (NSGA Ⅱ). The simulation experimental results show that the proposed algorithm can not only control the user cache within the specified threshold, but also effectively improve the user satisfaction and optimize the spectrum efficiency.

Key words: multi-beam satellite telecommunication, user satisfaction, spectrum efficiency, channel caching, simulated annealing-elitist non-dominated sorting genetic algorithm Ⅱ (SA-NSGA Ⅱ)

中图分类号:

TN911.7

饶悦, 杨健, 孙国敏, 张伟, 邵怀宗, 林静然. 基于改进SA-NSGAⅡ的多波束卫星动态资源分配方法[J]. 系统工程与电子技术, 2024, 46(12): 4222-4230.

Yue RAO, Jian YANG, Guomin SUN, Wei ZHANG, Huaizong SHAO, Jingran LIN. Multi-beam satellite dynamic resource allocation method based on improved SA-NSGAⅡ[J]. Systems Engineering and Electronics, 2024, 46(12): 4222-4230.

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参数名称	参数取值
用户总数	400
上行用户数	200
下行用户数	200
卫星总带宽/MHz	10
传播距离d/km	36 000
工作频率f/GHz	10
退火初始温度/K	500
限制缓存H_th/Mbps	2
退火迭代次数	5 000
遗传父代个数	200
交叉概率	0.8
变异概率	0.2
NSGAⅡ迭代次数	5 000

退火降温系数取值	用户满意度/%	堆积缓存/Mbps
0.65	82.73	1.98
0.70	85.32	1.97
0.75	86.65	1.97
0.80	87.13	1.96
0.85	87.72	1.96
0.90	86.98	1.96
0.95	85.23	1.97

载波个数取值	用户满意度/%	堆积缓存/Mbps
28	85.36	2.00
32	85.67	1.98
36	87.13	1.97
40	87.72	1.96
44	87.23	1.96
48	86.98	1.99
52	85.23	2.00

算法	缓存限制	迭代次数/次
算法	缓存限制	SA算法	NSGAⅡ
本文算法	H_th	5 000	5 000
算法1(SA-NSGAⅡ)	-	5 000	5 000
算法2(SA算法)	H_th	10 000	-
算法3(SA算法)	-	10 000	-

算法	H_t/Mbps	H节约比例/%	F/%	η_SE
本文算法	1.34	-	91.35	6.31
算法1	1.71	21.64	91.40	6.40
算法2	1.96	31.63	87.72	5.83
算法3	2.25	40.44	87.83	5.82

基于改进SA-NSGAⅡ的多波束卫星动态资源分配方法

Multi-beam satellite dynamic resource allocation method based on improved SA-NSGAⅡ

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