江帆;张兰;宫家志;

• 1:西安邮电大学陕西省信息通信网络及安全重点实验室
• 2:西安企鹅智媒科技有限公司

摘要(Abstract)：

面向蜂窝网络中基于设备对设备(device-to-device,D2D)多播的内容分发场景,为了有效减少分发能耗及延长网络生命周期,提出一种蜂窝网络中基于D2D多播的混合智能分簇簇略(hybrid intelligent clustering strategy,HICS)。该方案根据D2D用户对不同文件类型的偏好差异,使用自组织特征神经网络(self-organizing feature map,SOM)算法对用户进行聚类;再利用凝聚层次聚类算法(agglomerative hierarchical clustering algorithm,AHCA)对每个聚类内用户实现进一步的分簇;以最小化系统总能耗为目标,根据簇内用户的相对簇中心度、相对剩余能量、社交相似度以及距离因子等参数给出最佳的簇首选择算法。仿真结果表明,与已有方案相比,所提策略能够将具有相同文件偏好的用户更加均匀地分布在每个簇中,从而有效减少分发能耗,提高用户体验和系统性能。

关键词(KeyWords)： 设备到设备通信;分簇;自组织特征映射神经网络;凝聚层次聚类;系统能耗

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(62071377,61801382,61874087);; 陕西省自然科学重点基金项目(2019JZ-06);; 西安邮电大学大学生科技创新活动项目(19-B-289)

作者(Author): 江帆;张兰;宫家志;

Email:

DOI: 10.13682/j.issn.2095-6533.2020.04.005

参考文献(References)：

• [1] HOSSAIN E.5G cellular:Key enabling technologies and research challenges [J].IEEE Instrumentation & Measurement Magazine,2015,18(3):11-21.DOI:10.1109/mim.2015.7108393.
• [2] KU Y J,LIN D Y,5G radio access network design with the fog paradigm:Confluence of communications and computing[J].IEEE Communications Magazine,2017,55(4):46-52.DOI:10.1109/mcom.2017.1600893.
• [3] 张平,陶运铮,张治.5G若干关键技术评述[J].通信学报,2016(7):15-29.DOI:10.11959/j.issn.1000-436x.2016130.
• [4] LI M F,TSAI H L.Design and evaluation of a hybrid D2D discovery mechanism in 5G cellular networks.[C]//Proceedings of the 2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN).Prague,Czech Republic:IEEE,2018:241-243.DOI:10.1109/ icufn.2018.8436771.
• [5] XU X D,ZHANG Y ,SUN Z,et al.Analytical modeling of mode selection for moving D2D enabled cellular networks[J].IEEE Communications Letters,2016,20(6):1203-1206.DOI:10.1109/lcomm.2016.2552171.
• [6] ZHAO G G,CHEN S,QI L,et al.Mo-bile-traffic-aware offloading for energy-and spectral-efficient large-scale D2D-enabled cellular networks[J].IEEE Transactions on Wireless Communications,2019,18(6):3251-3264.DOI:10.1109/twc.2019.2912596.
• [7] LEE J,JAE H L.Performance analysis and resource allocation for cooperative D2D communication in cellular networks with multiple D2D pairs [J].IEEE Communications Letters,2019,23(5):909-912.DOI:10.1109/lcomm.2019.2907252.
• [8] XU Y ,LI X ,ZHANG J .Device-to-device content delivery in cellular networks:Multicast or unicast[J].IEEE Transactions on Vehicular Technology,2017,67(5):4401-4414.DOI:10.1109/tvt.2017.2787723.
• [9] 江帆,申斌艳,李晨碧.提高D2D多播能效的一种方案[J].西安邮电大学学报,2017,22(1):12-17.DOI:10.13682/j.issn.2095-6533.
• [10] REN F,WANG X.Joint social,energy and transfer rate to select cluster heads in D2D multicast communication [C]//Proceedings of the 2018 10th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA).Changsha:IEEE,2018:146-151.DOI:10.1109/icmtma.2018.00112.
• [11] MOHAMMAD G ,AHMED B.Self-organized scheduling re-quest for uplink 5G networks:A D2D clustering approach [J].IEEE Transactions on Communications.2018,67(2):1197-1209.DOI:10.1109/tcomm.2018.2876008.
• [12] LIANXIN Y,DAN W,SHIMING X ,et al.Social-energy-aware user clustering for content sharing based on D2D multicast communications [J].IEEE Access,2018,6:36092-36104.DOI:10.1109/access.2018.2849204.
• [13] UYOATA,MQHELE Robust multicast device-to-device communication[C]//Proceedings of the 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS).Indore India:IEEE,2018:1-6.DOI:10.1109/ants.2018.8710155.
• [14] ANUBHAV K ,ANIRUDH S J;RAMESH T K.Distance and energy aware device to device communication[C]//Proceedings of the 2019 International Conference on Communication and Signal Processing.Chennai India:IEEE,2019:522-525.DOI:10.1109/iccsp.2019.8698098.
• [15] UMI ,ALIAS,Mining of e-learning behavior using SOM clustering[C]// Proceedings of the Ict International Student Project Conference.Malaysia:IEEE,2017:1-4.DOI:10.1109/ict-ispc.2017.8075350.
• [16] KOMAL S,KHAN,YI Y,et al.On the application of agglomerative hierarchical clustering for cache-assisted D2D networks[C]//Proceedings of the 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC).Las Vegas:IEEE,2019:1-6.DOI:10.1109/ccnc.2019.8651785.