无人机辅助蜂窝网络中的无人机与用户协同缓存算法

doi:10.11959/j.issn.1000-436x.2020029

通信学报 ›› 2020, Vol. 41 ›› Issue (9): 130-138.doi: 10.11959/j.issn.1000-436x.2020029

无人机辅助蜂窝网络中的无人机与用户协同缓存算法

张天魁¹,陈超¹,王子端¹,杨鼎成²

¹ 北京邮电大学通信与信息工程学院，北京 100876
² 南昌大学信息工程学院，江西南昌 330031

修回日期:2020-07-23 出版日期:2020-09-25 发布日期:2020-10-12
作者简介:张天魁（1980- ），男，黑龙江哈尔滨人，博士，北京邮电大学教授、博士生导师，主要研究方向为应急通信网络技术、无人机通信网络、移动边缘计算与缓存、未来网络融合与管理、大规模天线与协作通信、无线资源管理技术等|陈超（1995- ），女，江苏南京人，北京邮电大学硕士生，主要研究方向为边缘缓存与无人机通信|王子端（1996- ），男，河北石家庄人，北京邮电大学硕士生，主要研究方向为无人机通信、非正交多址接入技术与边缘缓存|杨鼎成（1985- ），男，江西樟树人，博士，南昌大学教授、硕士生导师，主要研究方向为无人机通信、无线资源管理
基金资助:
国家自然科学基金资助项目(61971060)

Cooperative caching algorithm of UAV and user in UAV-assisted cellular network

Tiankui ZHANG¹,Chao CHEN¹,Ziduan WANG¹,Dingcheng YANG²

¹ School of Communication and Information Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China
² School of Information Engineering,Nanchang University,Nanchang 330031,China

Revised:2020-07-23 Online:2020-09-25 Published:2020-10-12
Supported by:
The National Natural Science Foundation of China(61971060)

摘要/Abstract

摘要：

针对无人机辅助蜂窝网络中的海量数据内容传输与无人机无线回程带宽受限这一矛盾，提出了一种无人机与用户协同缓存算法。通过在无人机以及用户设备上部署存储设备，将用户请求的热点内容缓存后进行共享分发，以减少无人机回程链路资源与能量开销，减轻业务负载并降低用户时延。以用户内容获取时延最小化为目标建立了无人机与用户缓存联合优化问题，将其分解为无人机缓存子问题与用户缓存子问题，并分别基于交替方向乘子法和全局贪婪算法进行求解，通过迭代获得收敛的优化结果，实现了无人机与用户的协同缓存。仿真结果表明，所提算法能够有效降低用户的内容获取时延，提升系统性能。

关键词: 边缘缓存, 无人机通信, 无人机辅助蜂窝网络, 协同缓存

Abstract:

Aiming at the problem of mass data content transmission and limited wireless backhaul resource of UAV in UAV-assisted cellular network,a cooperative caching algorithm for cache-enabled UAV and user was proposed.By deploying caches on UAV and user device,the popular content requested by user was cached and delivered,which alleviated the backhaul resource and energy consumption of UAV,reduced the traffic load and user delay.A joint optimization problem of UAV and user caching was established with the goal of minimizing user content acquisition delay,and decomposed into UAV caching sub-problem and user caching sub-problem,which were solved based on alternating direction method of multiplier and global greedy algorithm respectively.The iterative way was used to obtain convergent optimization result,and the cooperative caching of UAV and user was realized.Simulation results show that the proposed algorithm can effectively reduce user content acquisition delay and improve system performance.

Key words: edge caching, UAV communication, UAV-assisted cellular network, cooperative caching

中图分类号:

TP393

张天魁,陈超,王子端,杨鼎成. 无人机辅助蜂窝网络中的无人机与用户协同缓存算法[J]. 通信学报, 2020, 41(9): 130-138.

Tiankui ZHANG,Chao CHEN,Ziduan WANG,Dingcheng YANG. Cooperative caching algorithm of UAV and user in UAV-assisted cellular network[J]. Journal on Communications, 2020, 41(9): 130-138.

图/表 5

参考文献 13

[1]	SHARMA V , BENNIS M , KUMAR R . UAV-assisted heterogeneous networks for capacity enhancement[J]. IEEE Communications Letters, 2016,20(6): 1207-1210.
[2]	张天魁, 单思洋, 许晓耕 ,等. 信息中心网络缓存技术研究综述[J]. 北京邮电大学学报, 2016,39(3): 1-15.
	ZHANG T K , SHAN S Y , XU X G ,et al. Survey on caching techniques of information centric networking[J]. Journal of Beijing University of Posts and Telecommunications, 2016,39(3): 1-15.
[3]	CHEN M Z , MOZAFFARI M , SAAD W ,et al. Caching in the sky:proactive deployment of cache-enabled unmanned aerial vehicles for optimized quality-of-experience[J]. IEEE Journal on Selected Areas in Communications, 2017,35(5): 1046-1061.
[4]	ZHAO N , YU F R , FAN L ,et al. Caching unmanned aerial vehicle-enabled small-cell networks:employing energy-efficient methods that store and retrieve popular content[J]. IEEE Vehicular Technology Magazine, 2019,14(1): 71-79.
[5]	HUANG W , YANG Z , PAN C ,et al. Joint power,altitude,location and bandwidth optimization for UAV with underlaid D2D communications[J]. IEEE Wireless Communications Letters, 2019,8(2): 524-527.
[6]	ZHANG L , XIAO M , WU G ,et al. Efficient scheduling and power allocation for D2D-assisted wireless caching networks[J]. IEEE Transactions on Communications, 2016,64(6): 2438-2452.
[7]	ZHANG T K , FANG X Y , LIU Y W ,et al. D2D-enabled mobile user edge caching:a multi-winner auction approach[J]. IEEE Transactions on Vehicular Technology, 2019,68(12): 12314-12328.
[8]	XU X L , ZENG Y , GUAN Y L ,et al. Overcoming endurance issue:UAV-enabled communications with proactive caching[J]. IEEE Journal on Selected Areas in Communications, 2018,36(6): 1231-1244.
[9]	AL-HOURANI A , KANDEEPAN S , JAMALIPOUR A . Modeling air-to-ground path loss for low altitude platforms in urban environments[C]// 2014 IEEE Global Communications Conference (GLOBECOM). Piscataway:IEEE Press, 2014: 2898-2904.
[10]	3GPP.Evolved universal terrestrial radio access (E-UTRA); further advancements for E-UTRA physical layer aspects:TR 36.814-920[S].(2017)[2020-04-23].
[11]	FAN H M , ZHANG T K , LOO J ,et al. Caching deployment algorithm based on user preference in device-to-device networks[C]// 2017 IEEE Global Communications Conference (GLOBECOM). Piscataway:IEEE Press, 2017: 1-6.
[12]	ZHENG Z J , SONG L Y , HAN Z ,et al. A stackelberg game approach to proactive caching in large-scale mobile edge networks[J]. IEEE Transactions on Wireless Communications, 2018,17(8): 5198-5211.
[13]	KANGASHARJU J , ROBERTS J , ROSS K W . Object replication strategies in content distribution networks[J]. Journal of Computer Communications, 2002,25: 376-383.

无人机辅助蜂窝网络中的无人机与用户协同缓存算法

Cooperative caching algorithm of UAV and user in UAV-assisted cellular network

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 5

参考文献 13

相关文章 9

Metrics

推荐阅读 0

[1]	朱思峰, 蔡江昊, 柴争义, 孙恩林. 车联网云边协同计算场景下的多目标优化卸载决策[J]. 通信学报, 2022, 43(6): 223-234.
[2]	郎磊, 王荆宁, 王一, 赵子涛. 无人机辅助通信中基于用户轨迹的无线资源和航迹优化[J]. 通信学报, 2022, 43(3): 225-232.
[3]	肖振宇, 刘珂, 朱立鹏. 无人机机间毫米波阵列通信技术[J]. 通信学报, 2022, 43(10): 196-209.
[4]	李斌, 刘文帅, 谢万城, 费泽松. 智能反射面赋能无人机边缘网络计算卸载方案[J]. 通信学报, 2022, 43(10): 223-233.
[5]	李方伟, 张海波, 王子心. 车联网中基于MEC的V2X协同缓存和资源分配[J]. 通信学报, 2021, 42(2): 26-36.
[6]	任佳智,田辉,范绍帅,林远卓,聂高峰,李继龙. 基于用户偏好预测的无人机部署和缓存策略[J]. 通信学报, 2020, 41(6): 1-13.
[7]	吴启晖,吴伟. 无人机辅助边缘计算的能量效率最大化算法设计[J]. 通信学报, 2020, 41(10): 15-24.
[8]	张果,胡宇翔,黄万伟,汪斌强,曹路佳. 基于流行内容感知和跟踪的协同缓存策略[J]. 通信学报, 2017, 38(2): 132-142.
[9]	刘银龙,汪敏,马伟,周旭,胡亚辉. P2P缓存系统中总开销最小的协作缓存策略[J]. 通信学报, 2015, 36(3): 187-194.