Resource Allocation Algorithm of Space-Air-Ground Integrated Network for Dense Scenarios

ZHANG Hong; LIAO Yuxin; WANG Ruyan; WU Dapeng; DU Huimin

doi:10.11999/JEIT231086

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ZHANG Hong, LIAO Yuxin, WANG Ruyan, WU Dapeng, DU Huimin. Resource Allocation Algorithm of Space-Air-Ground Integrated Network for Dense Scenarios[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231086

Citation:

ZHANG Hong, LIAO Yuxin, WANG Ruyan, WU Dapeng, DU Huimin. Resource Allocation Algorithm of Space-Air-Ground Integrated Network for Dense Scenarios[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231086

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Resource Allocation Algorithm of Space-Air-Ground Integrated Network for Dense Scenarios

doi: 10.11999/JEIT231086

1.
School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Advanced Network and Intelligent Connection Technology Key Laboratory of Chongqing Education Commission of China, Chongqing 400065, China
3.
Chongqing Key Laboratory of Ubiquitous Sensing and Networking, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (62271096, U20A20157), Science and Technology Research Program of Chongqing Municipal Education Commission (KJQN202000626), University Innovation Research Group of Chongqing (CXQT20017), Youth Innovation Group Support Program of ICE Discipline of CQUPT (SCIE-QN-2022-04), Chongqing Postdoctoral Science Special Foundation (2021XM3058), Natural Science Foundation of Chongqing, China (CSTB2023NSCQ-LZX0134)

Received Date: 2023-10-08
Rev Recd Date: 2024-04-08

Available Online: 2024-05-01

Abstract

Abstract

Space-air-ground integrated network has the advantages of extensive coverage, high throughput, and strong elasticity. A resource allocation algorithm for dense scenarios is proposed to solve the problems of network congestion and deterioration of service quality caused by concurrent access of many users and network load imbalance. Firstly, the user utility function is constructed based on the user demand and the preferences of different types of user tasks. Then, load balancing is realized based on the matching game network selection algorithm and the power control algorithm combined with the dual ascending method, and the resource allocation scheme is optimized. Experimental results show that compared with the traditional strategy, the proposed strategy increases the overall user access rate by at least 35%, and improves the performance of delay and throughput by more than 50%. Load balancing is more effective in dense scenarios and network performance is improved.
- Space-Air-Ground Integrated Network (SAGIN),
- Resource allocation,
- Game theory,
- Dense scenarios

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References(19)

References

[1]	WU Dapeng, SI Shushan, WU Shaoen, et al. Dynamic trust relationships aware data privacy protection in mobile crowd-sensing[J]. IEEE Internet of Things Journal, 2018, 5(4): 2958–2970. doi: 10.1109/JIOT.2017.2768073.
[2]	WU Dapeng, LIU Qianru, WANG Honggang, et al. Socially aware energy-efficient mobile edge collaboration for video distribution[J]. IEEE Transactions on Multimedia, 2017, 19(10): 2197–2209. doi: 10.1109/TMM.2017.2733300.
[3]	陈新颖, 盛敏, 李博, 等. 面向6G的无人机通信综述[J]. 电子与信息学报, 2022, 44(3): 781–789. doi: 10.11999/JEIT210789. CHEN Xinying, SHENG Min, LI Bo, et al. Survey on unmanned aerial vehicle communications for 6G[J]. Journal of Electronics & Information Technology, 2022, 44(3): 781–789. doi: 10.11999/JEIT210789.
[4]	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): 1–19. doi: 10.11959/j.issn.2096-3750.2020.00142. SHEN Xuemin, CHENG Nan, ZHOU Haibo, et al. Space-air-ground integrated networks: Review and prospect[J]. Chinese Journal on Internet of Things, 2020, 4(3): 1–19. doi: 10.11959/j.issn.2096-3750.2020.00142.
[5]	徐晓斌, 王琪, 范存群, 等. 面向空天地一体化信息网络的边缘计算资源融合管理方法[J]. 计算机学报, 2023, 46(4): 690–710. doi: 10.11897/SP.J.1016.2023.00690. XU Xiaobin, WANG Qi, FAN Cunqun, et al. An aggregated edge computing resource management method for space-air-ground integrated information networks[J]. Chinese Journal of Computers, 2023, 46(4): 690–710. doi: 10.11897/SP.J.1016.2023.00690.
[6]	HE Jingchao, CHENG Nan, YIN Zhisheng, et al. Service-oriented network resource orchestration in space-air-ground integrated network[J]. IEEE Transactions on Vehicular Technology, 2024, 73(1): 1162–1174. doi: 10.1109/TVT.2023.3301676.
[7]	GUO Chao, GONG Cheng, XU Haitao, et al. A dynamic handover software-defined transmission control scheme in space-air-ground integrated networks[J]. IEEE Transactions on Wireless Communications, 2022, 21(8): 6110–6124. doi: 10.1109/TWC.2022.3146452.
[8]	CAO Bin, ZHANG Jintong, LIU Xin, et al. Edge–cloud resource scheduling in space–air–ground-integrated networks for internet of vehicles[J]. IEEE Internet of Things Journal, 2022, 9(8): 5765–5772. doi: 10.1109/JIOT.2021.3065583.
[9]	SUN Jinlong, LIU Fan, ZHOU Yuzhi, et al. Surveillance plane aided air-ground integrated vehicular networks: Architectures, applications, and potential[J]. IEEE Wireless Communications, 2020, 27(6): 122–128. doi: 10.1109/MWC.001.2000079.
[10]	LI Ruidong, MATSUZONO K, ASAEDA H, et al. Achieving high throughput for heterogeneous networks with consecutive caching and adaptive retrieval[J]. IEEE Transactions on Network Science and Engineering, 2020, 7(4): 2443–2455. doi: 10.1109/TNSE.2020.3010939.
[11]	ZHU Yun, LI Jiade, HUANG Qiuyuan, et al. Game theoretic approach for network access control in heterogeneous networks[J]. IEEE Transactions on Vehicular Technology, 2018, 67(10): 9856–9866. doi: 10.1109/TVT.2018.2856752.
[12]	FAN Kexin, FENG Bowen, ZHANG Xilin, et al. Network selection based on evolutionary game and deep reinforcement learning in space-air-ground integrated network[J]. IEEE Transactions on Network Science and Engineering, 2022, 9(3): 1802–1812. doi: 10.1109/TNSE.2022.3153480.
[13]	CHEN Qian, MENG Weixiao, HAN Shuai, et al. Service-oriented fair resource allocation and auction for civil aircrafts augmented space-air-ground integrated networks[J]. IEEE Transactions on Vehicular Technology, 2020, 69(11): 13658–13672. doi: 10.1109/TVT.2020.3021423.
[14]	谭诗翰, 金凤林, 顿聪颖. 面向用户需求的空天地一体化车载网络任务分配策略[J]. 系统工程与电子技术, 2022, 44(5): 1717–1727. doi: 10.12305/j.issn.1001-506X.2022.05.35. TAN Shihan, JIN Fenglin, and DUN Congying. Task assignment strategy for space-air-ground integrated vehicular networks oriented to user demand[J]. Systems Engineering and Electronics, 2022, 44(5): 1717–1727. doi: 10.12305/j.issn.1001-506X.2022.05.35.
[15]	3GPP. TS 38.901 Study on channel model for frequencies from 0.5 to 100 GHz[EB/OL]. https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=3173, 2022.
[16]	GU Shushi, SUN Xinyi, YANG Zhihua, et al. Energy-aware coded caching strategy design with resource optimization for satellite-UAV-vehicle-integrated networks[J]. IEEE Internet of Things Journal, 2022, 9(8): 5799–5811. doi: 10.1109/JIOT.2021.3065664.
[17]	ZENG Yong, XU Jie, and ZHANG Rui. Energy minimization for wireless communication with rotary-wing UAV[J]. IEEE Transactions on Wireless Communications, 2019, 18(4): 2329–2345. doi: 10.1109/TWC.2019.2902559.
[18]	GOYAL R K and KAUSHAL S. Network selection using AHP for fast moving vehicles in heterogeneous networks[M]. CHAKI R, CORTESI A, SAEED K, et al. Advanced Computing and Systems for Security: Volume 1. New Delhi: Springer, 2016: 235–243. doi: 10.1007/978-81-322-2650-5_15.
[19]	张红旗, 黄睿, 常德显. 一种基于匹配博弈的服务链协同映射方法[J]. 电子与信息学报, 2019, 41(2): 385–393. doi: 10.11999/JEIT180385. ZHANG Hongqi, HUANG Rui, and CHANG Dexian. A collaborative mapping method for service chain based on matching game[J]. Journal of Electronics & Information Technology, 2019, 41(2): 385–393. doi: 10.11999/JEIT180385.