物联网学报 ›› 2019, Vol. 3 ›› Issue (1): 14-19.doi: 10.11959/j.issn.2096-3750.2019.00086

• 理论与技术 • 上一篇    下一篇

分簇认知物联网联合资源分配算法

刘鑫   

  1. 大连理工大学信息与通信工程学院,辽宁 大连 116024
  • 修回日期:2019-02-22 出版日期:2019-03-01 发布日期:2019-04-04
  • 作者简介:刘鑫(1984- ),男,黑龙江哈尔滨人,博士,大连理工大学副教授、硕士生导师,主要研究方向为认知无线电、传感器网络和物联网等。
  • 基金资助:
    国家自然科学基金资助项目(61601221);国家自然科学基金委员会—中国民用航空局民航联合研究基金资助项目(U1833102)

Joint resource allocation algorithm for clustering cognitive Internet of things

Xin LIU   

  1. School of Information and Communication Engineering,Dalian University of Technology,Dalian 116024,China
  • Revised:2019-02-22 Online:2019-03-01 Published:2019-04-04
  • Supported by:
    The National Natural Science Foundations of China(61601221)

摘要:

认知物联网通过频谱感知和共享有效提高了频谱利用率,但频谱感知会产生开销。提出分簇认知物联网降低感知开销,通过联合资源分配提高物联网的传输速率。首先提出分簇认知物联网的网络模型和帧结构,推导物联网的平均传输速率和干扰功率;然后建立优化模型,通过联合优化感知时间、感知簇头和传输功率使传输速率最大化,并给出联合优化算法求解;最后提出认知物联网的节点分簇和簇头选择算法。仿真结果表明,所提方案通过联合资源分配能够获得最大传输速率,且与传统方案相比,传输性能有所提高。

关键词: 认知物联网, 分簇, 资源分配, 协作频谱感知, 传输速率

Abstract:

Cognitive Internet of things (CIoT) can improve spectrum utilization effectively through spectrum sensing and sharing,but spectrum sensing may generate overhead.Clustering CIoT was proposed to decrease sensing overhead,whose transmission rate could be improved through joint resource allocation.The network model and frame structure of the CIoT were proposed firstly,and the average transmission rate and interference power of the CIoT were deduced.Then,an optimization model was built to maximize the transmission rate through jointly optimizing the sensing time,sensing cluster head and transmission power,and a joint optimization algorithm was given to solve the optimization problem.Finally,the node clustering and cluster head selection algorithm of the CIoT was presented.The simulations show that the maximal transmission rate through joint resource allocation can be achieved and the transmission performance compared with the traditional schemes can be improved by the proposed scheme.

Key words: cognitive Internet of things, clustering, resource allocation, cooperative spectrum sensing, transmission rate

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