星地融合网络中基于多目标优化的星间切换决策方法

doi:10.11959/j.issn.2096-8930.2023031

Abstract

Abstract:

The high-speed motion of low-earth orbit communication satellites results in a highly dynamic network topology, and the spatio-temporal distribution of resources in the satellite-terrestrial integrated network is non-uniform.When multiple users and services switch between satellites, a large number of handover requests are triggered, leading to intensified network resource competition.As a result, the limited satellite resources cannot meet all the handover requests, leading to a significant decrease in handover success rate.In view of the above problem, the multi-objective optimization based satellite handover method was proposed.It introduced the satellite coverage spatio-temporal graph and transforms the dynamic continuous topology into static discrete snapshots, accurately depicted the connections between satellite nodes and users at different times and locations.The multi-objective optimization model was established for satellite handover decisions, and anadaptive accelerated multi-objective evolutionary algorithm(AAMOEA) was proposed to optimized user data rate and network load simultaneously, ensured handover success rate and enhanced network service capability.It built a STIN communication simulation environment and tested the multi user handover performance in a multi satellite overlapping coverage scenario.The results demonstrated that the multi-objective optimization-based satellite handover method achieved an average handover success rate improvement of over 20% compared to benchmark algorithms.

Key words: satellite-terrestrial integrated network, handover control, network topology, multi-objective optimization

CLC Number:

TP393

Renpeng LIU, Bo HU, Hequn LI. Inter-Satellite Handover Method Based Multi-Objective Optimization in Satellite-Terrestrial Integrated Network[J]. Space-Integrated-Ground Information Networks, 2023, 4(3): 59-66.

Figures/Tables 9

References 26

[1]	ZHU X M , JIANG C X . Integrated satellite-terrestrial networks toward 6G:architectures,applications,and challenges[J]. IEEE Internet of Things Journal, 2022,9(1): 437-461.
[2]	陈山枝 . 关于低轨卫星通信的分析及我国的发展建议[J]. 电信科学, 2020,36(6): 1-13.
	CHEN S Z . Analysis of LEO satellite communication and suggestions for its development strategy in China[J]. Telecommunications Science, 2020,36(6): 1-13.
[3]	沈学民, 承楠, 周海波 ,等. 空天地一体化网络技术:探索与展望[J]. 物联网学报, 2020,4(3): 3-19.
	SHEN X M , CHENG N , ZHOU H B ,et al. Space-air-ground integrated networks:review and prospect[J]. Chinese Journal on Internet of Things, 2020,4(3): 3-19.
[4]	CHEN S Z , SUN S H , KANG S L . System integration of terrestrial mobile communication and satellite communication—the trends,challenges and key technologies in B5G and 6G[J]. China Communications, 2020,17(12): 156-171.
[5]	CHOWDHURY P K , ATIQUZZAMAN M , IVANCIC W . Handover schemes in satellite networks:state-of-the-art and future research directions[J]. IEEE Communications Surveys ＆ Tutorials, 2006,8(4): 2-14.
[6]	ZHOU D , SHENG M , LI J D ,et al. Aerospace integrated networks innovation for empowering 6G:asurvey and future challenges[J]. IEEE Communications Surveys ＆ Tutorials, 2023,25(2): 975-1019.
[7]	HOZAYEN M , DARWISH T , KURT G K ,et al. A graph-based customizable handover framework for LEO satellite networks[C]// 2022 IEEE Globecom Workshops. Piscataway:IEEE Press, 2022: 868-873.
[8]	FENG L , LIU Y F , WU L ,et al. A satellite handover strategy based on MIMO technology in LEO satellite networks[J]. IEEE Communications Letters, 2020,24(7): 1505-1509.
[9]	WU Z F , JIN F L , LUO J X ,et al. A graph-based satellite handover framework for LEO satellite communication networks[J]. IEEE Communications Letters, 2016,20(8): 1547-1550.
[10]	LYU X Y , WU S H , LI A M ,et al. A weighted graph-based handover strategy for aeronautical traffic in LEO SatCom networks[J]. IEEE Networking Letters, 2022,4(3): 132-136.
[11]	HE S , WANG T , WANG S . Load-aware satellite handover strategy based on multi-agent reinforcement learning[C]// GLOBECOM 2020 - 2020 IEEE Global Communications Conference. Piscataway:IEEE Press, 2020: 1-6.
[12]	WANG J , MU W , LIU Y ,et al. Deep reinforcement learning-based satellite handover scheme for satellite communications[C]// 2021 13th International Conference on Wireless Communications and Signal Processing (WCSP). Piscataway:IEEE Press, 2021: 1-6.
[13]	XU H H , LI D S , LIU M L ,et al. QoE-driven intelligent handover for user-centric mobile satellite networks[J]. IEEE Transactions on Vehicular Technology, 2020,69(9): 10127-10139.
[14]	WU Y , HU G Y , JIN F L ,et al. A satellite handover strategy based on the potential game in LEO satellite networks[J]. IEEE Access, 2019,7: 133641-133652.
[15]	ZHU A Q , GUO S T , LIU B ,et al. Adaptive multiservice heterogeneous network selection scheme in mobile edge computing[J]. IEEE Internet of Things Journal, 2019,6(4): 6862-6875.
[16]	SEYEDI Y , SAFAVI S M . On the analysis of random coverage time in mobile LEO satellite communications[J]. IEEE Communications Letters, 2012,16(5): 612-615.
[17]	JIANG F , ZHANG Q Y , YANG Z H ,et al. A space-time graph based multipath routing in disruption-tolerant earth-observing satellite networks[J]. IEEE Transactions on Aerospace and Electronic Systems, 2019,55(5): 2592-2603.
[18]	KIBINDA N M , GE X H . User-centric cooperative transmissions-enabled handover for ultra-dense networks[J]. IEEE Transactions on Vehicular Technology, 2022,71(4): 4184-4197.
[19]	DAI C Q , XU J , WU J ,et al. Multi-objective Intelligent Handover in Satellite-Terrestrial Integrated Networks[C]// 2022 IEEE International Conference on Communications Workshops (ICC Workshops). Piscataway:IEEE Press, 2022: 367-372.
[20]	LI J , XUE K P , LIU J Q ,et al. A user-centric handover scheme for ultra-dense LEO satellite networks[J]. IEEE Wireless Communications Letters, 2020,9(11): 1904-1908.
[21]	LI F , WAN Q H , HE Q E ,et al. An improved many-objective evolutionary algorithm for multi-satellite joint large regional coverage[J]. IEEE Access, 2023,11: 45838-45849.
[22]	DEB K , PRATAP A , AGARWAL S ,et al. A fast and elitist multiobjective genetic algorithm:NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002,6(2): 182-197.
[23]	YU H , ZHAN J , LI B J ,et al. Load balancing strategy for wireless multi-hotspot networks based on improved NSGA-II algorithm[C]// 2022 International Conference on Networking and Network Applications (NaNA). Piscataway:IEEE Press, 2022: 107-112.
[24]	WAGNER M , NEUMANN F . A fast approximation-guided evolutionary multi-objective algorithm[C]// Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation. Amsterdam:ACM, 2013: 687-694.
[25]	DENG Z L , QI H , WU C F ,et al. A cluster positioning architecture and relative positioning algorithm based on pigeon flock bionics[J]. Satellite Navigation, 2023,4(1): 1-21.
[26]	ZHU Y , QIN Y , YANG D ,et al. An enhanced decomposition-based multi-objective evolutionary algorithm with a self-organizing collaborative scheme[J]. Expert Systems with Applications, 2023,213:118915.

Metrics

Recommended 0

No Suggested Reading articles found!

方法分类	算法	场景	优化目标	关键技术点
基于图论	GBH＆MADM	高速航空交通	整体吞吐量	设置信道保留顺序(CRO)参数
基于图论	加权二分图＆KM	馈电链路切换控制	馈电链路速率	MIMO系统多阶最大权重匹配
基于学习	RL	随机接入用户	切换次数、端到端时延	利用空间关系耦合模型预测切换因素
基于学习	RL	多LEO卫星覆盖用户	用户阻塞率	分布式多智能体切换
基于博弈	二分图＆势博弈	高低轨卫星网络协同覆盖的地面用户	切换次数	基于SDSN结构的势博弈算法

参数名称		仿真设置
	星座类型	Starlink星座
	卫星数	1 584颗
	轨道面数	72个
卫星仿真环境	轨道倾角	53°
	轨道高度	550 km
	系统带宽	100 MHz
	用户数量	40～140个
	种群大小	100
算法设置	编码长度	40～140
	迭代次数	100次

Inter-Satellite Handover Method Based Multi-Objective Optimization in Satellite-Terrestrial Integrated Network

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 9

References 26

Related Articles 3

Metrics

Recommended 0

[1]	Zihao PAN, Chen XIE, Heng WANG, Daoxing GUO. Research Status of CPM for Satellite-Terrestrial Integrated Network [J]. Space-Integrated-Ground Information Networks, 2023, 4(1): 42-49.
[2]	Bensi ZHANG, Deyi PENG, Yun LI. Beamforming for Non-Orthogonal Multicast and Unicast Transmissions Based on Rate Splitting in Satellite-Terrestrial Integrated Network [J]. Space-Integrated-Ground Information Networks, 2022, 3(4): 75-82.
[3]	Fuxiang ZHU,Chenghao HU,Yan LIU,Hui SUN,Jianzhao TIAN,Zhou LU. Link Status Monitoring Technology for the Heterogeneous Network [J]. Space-Integrated-Ground Information Networks, 2020, 1(1): 48-53.