期刊文献+

异构网络中D2D资源分配算法 被引量:3

D2D resource allocation algorithm in heterogeneous networks
下载PDF
导出
摘要 针对蜂窝用户和终端直通(D2D)用户构成的异构网络中频谱资源利用率低和同频干扰严重的问题,提出了一种新的资源分配方案。为限制D2D用户对基站接收蜂窝用户信号产生干扰,提出了基站端保护区域的概念,通过对保护区域外的D2D用户进行分组,减小了D2D用户链路间的相互干扰,并实现了多个D2D用户复用一个蜂窝用户上行资源进行通信的场景,最后,基于中断概率为每个D2D用户分组选择蜂窝用户资源进行复用,以保证蜂窝用户的通信质量。仿真结果表明:所提算法不仅可以有效降低用户之间的同频干扰,还可以允许更多的D2D用户接入,提高系统吞吐量,并提升系统公平性。 In order to solve the low utilization of spectrum resources problem and co-channel interference problem in heterogeneous network composed of cellular users and device-to-device(D2D)users,a new resource allocation scheme is proposed.To limit the interference of the D2D users to the receiving of the cellular user signals by the base station,the concept of the protection area of the base station is proposed.And then the D2D users outside the protected area are grouped,thereby reduce the mutual interference between the D2D user links,and achieve more D2D user multiplexes a cellular user uplink resource for communication.Finally,Selecting cellular user resources for multiplexing for each D2D user group based on the outage probability,to ensure the communication quality of the cellular user.The simulation results show that the proposed algorithm not only can effectively reduce the co-channel interference between users,but also allows more D2D users to access,improve system throughput and improve system fairness.
作者 薛建彬 郭玉晶 XUE Jianbin;GUO Yujing(College of Computer and Communication,Lanzhou University of Technology,Lanzhou 730050,China;National Mobile Communications Research Laboratory,Southeast University,Nanjing 210096,China)
出处 《传感器与微系统》 CSCD 2020年第2期128-131,共4页 Transducer and Microsystem Technologies
基金 国家自然科学基金资助项目(61461026) 东南大学移动通信国家重点实验室开放研究基金资助项目(2014D13)
关键词 终端直通(D2D) 资源分配 区域 模糊聚类 吞吐量 公平性 device-to-device(D2D) resource allocation area fuzzy clustering throughput fairness
  • 相关文献

参考文献1

二级参考文献13

  • 1张敏,于剑.基于划分的模糊聚类算法[J].软件学报,2004,15(6):858-868. 被引量:176
  • 2张新波.两阶段模糊C-均值聚类算法[J].电路与系统学报,2005,10(2):117-120. 被引量:21
  • 3尹中航,唐元钢,孙富春,孙增圻.Fuzzy Clustering with Novel Separable Criterion[J].Tsinghua Science and Technology,2006,11(1):50-53. 被引量:4
  • 4Bezdek J C. Pattern Recognition with Fuzzy Objective Function Algorithms[M]. Plenum Press, NewYork, 1981
  • 5Duda R, Hart P, Stork D. Pattern Classification ( 2 nd Edition ) [M]. New York,USA:John Wiley& Sons,2001
  • 6Rose K, Gurewitz E, FoxGC. Constrained clustering as optimization method[J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1993,15(8) : 785-794
  • 7Krishnapuram R,Keller J M. A possibilistic approach to cluste ring[J]. IEEE Trans. Fuzzy Systems, 1993,1 (2) : 98-110
  • 8Timm H, Kruse R. A modification to improve possibilistic fuzzy cluster analysis[C]//Proc, of the 2002 IEEE Int'l Conf. on Fuzzy Systems, (2). Honululu: IEEE, 2002 : 1460-1465
  • 9Timm H, Borgelt C, Dorring C, et al. Fuzzy cluster analysis with cluster repulsion[C]//Proc. of the Eruopean Syrup. On Intelligent Technologies, Tenerife. 2001. CD-ROM
  • 10Ozdemir D, Akarun L. Fuzzy algorithms for combined quantization and dithering[J]. IEEE Trans. Image Processing, 2001,10 (6):923-931

共引文献67

同被引文献13

引证文献3

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部