通信学报 ›› 2020, Vol. 41 ›› Issue (6): 1-13.doi: 10.11959/j.issn.1000-436x.2020104
• 学术论文 • 下一篇
任佳智1,田辉1(),范绍帅1,林远卓1,聂高峰1,李继龙2
修回日期:
2020-04-14
出版日期:
2020-06-25
发布日期:
2020-07-04
作者简介:
任佳智(1987- ),男,吉林省吉林市人,北京邮电大学博士生,主要研究方向为边缘缓存、网络切片、复杂网络|田辉(1963- ),女,河南郑州人,博士,北京邮电大学教授、博士生导师,主要研究方向为自组织网络、无线资源管理|范绍帅(1987- ),男,山东烟台人,博士,北京邮电大学讲师,主要研究方向为B5G组网及关键技术|林远卓(1998- ),男,黑龙江哈尔滨人,北京邮电大学硕士生,主要研究方向为边缘缓存与区块链技术|聂高峰(1988- ),男,河南周口人,博士,北京邮电大学讲师,主要研究方向为5G、6G系统关键技术及移动自组织网络|李继龙(1976- ),男,河北邯郸人,博士,国家广播电视总局教授级高工,主要研究方向为5G广播、广播电视融合网、无线数字广播、信道编码和调制技术等
基金资助:
Jiazhi REN1,Hui TIAN1(),Shaoshuai FAN1,Yuanzhuo LIN1,Gaofeng NIE1,Jilong LI2
Revised:
2020-04-14
Online:
2020-06-25
Published:
2020-07-04
Supported by:
摘要:
针对蜂窝网络中的缓存问题,考虑用户内容请求的空间异构性及时间波动性,提出了一种基于单个用户内容偏好预测的蜂窝网中无人机位置部署及缓存内容部署方案。首先基于用户的历史上下文信息,利用文件相似性及用户相似性来预测每个用户的内容偏好特性,并使用一种基于线性回归的方法来预测用户未来发起内容请求时的位置和时间;然后根据预测的地理位置、请求时间和内容偏好,分别利用基于自组织映射神经网络(SOM)的聚类算法和基于凝聚嵌套(AGNES)的分簇算法设计无人机的部署位置,并根据相应的无人机位置设计内容部署方案。仿真结果表明,所提算法在缓存命中率和时延性能上均优于对比算法。对真实数据集的分析结果表明,不同的用户特征对内容偏好影响权重不等,因此需要对不同的用户特征赋予合理的权值。
中图分类号:
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.
Jiazhi REN,Hui TIAN,Shaoshuai FAN,Yuanzhuo LIN,Gaofeng NIE,Jilong LI. UAV deployment and caching scheme based on user preference prediction[J]. Journal on Communications, 2020, 41(6): 1-13.
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