Dynamic spectrum allocation algorithm based on matching scheme for smart grid communication network

Suhong Yang, Jinkuan Wang, Yinghua Han, Xiuli Jiang
{"title":"Dynamic spectrum allocation algorithm based on matching scheme for smart grid communication network","authors":"Suhong Yang, Jinkuan Wang, Yinghua Han, Xiuli Jiang","doi":"10.1109/COMPCOMM.2016.7925250","DOIUrl":null,"url":null,"abstract":"Each part of smart grid system is supported by communications network. The amount of smart grid data is developing larger and more complex so that the network faces a lot of challenges to acquire stable and efficient communication in smart grid. The application of cognitive radio can effectively alleviate the shortage of spectrum resources in the smart grid communication network. In this paper, the spectrum allocation scheme of matching algorithm is proposed based on channel idle time and users' priority. Firstly, hidden Markov-model (HMM) is established to predict the idle time of channels in spectrum pool. Baum-Welch, which is the HMM training algorithm of the most commonly used, is formulated to train HMM parameter for each channel to get the most suitable HMM. Secondly, the data of smart grid is divided considering real-time priority, making the higher priority second user (SU) can occupy the channel with longer idle time. Finally, the system total throughput is calculated based on the two factors above. Simulation results show that the total throughput is improved effectively employing the matching algorithm and the stability and the reliability of communication network is obtained. The utilization of spectrum resources is also improved in smart grid.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPCOMM.2016.7925250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Each part of smart grid system is supported by communications network. The amount of smart grid data is developing larger and more complex so that the network faces a lot of challenges to acquire stable and efficient communication in smart grid. The application of cognitive radio can effectively alleviate the shortage of spectrum resources in the smart grid communication network. In this paper, the spectrum allocation scheme of matching algorithm is proposed based on channel idle time and users' priority. Firstly, hidden Markov-model (HMM) is established to predict the idle time of channels in spectrum pool. Baum-Welch, which is the HMM training algorithm of the most commonly used, is formulated to train HMM parameter for each channel to get the most suitable HMM. Secondly, the data of smart grid is divided considering real-time priority, making the higher priority second user (SU) can occupy the channel with longer idle time. Finally, the system total throughput is calculated based on the two factors above. Simulation results show that the total throughput is improved effectively employing the matching algorithm and the stability and the reliability of communication network is obtained. The utilization of spectrum resources is also improved in smart grid.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于匹配方案的智能电网通信网络动态频谱分配算法
智能电网系统的各个组成部分都有通信网络的支持。随着智能电网数据量的不断增大和复杂化,如何在智能电网中实现稳定、高效的通信面临着诸多挑战。认知无线电的应用可以有效缓解智能电网通信网络中频谱资源短缺的问题。本文提出了基于信道空闲时间和用户优先级的匹配算法频谱分配方案。首先,建立隐马尔可夫模型来预测频谱池中信道的空闲时间;提出了最常用的HMM训练算法Baum-Welch,对每个信道的HMM参数进行训练,得到最合适的HMM。其次,考虑实时优先级对智能电网的数据进行划分,使优先级较高的第二用户(SU)可以占用空闲时间较长的信道。最后,根据上述两个因素计算系统的总吞吐量。仿真结果表明,该匹配算法有效地提高了总吞吐量,保证了通信网络的稳定性和可靠性。智能电网也提高了频谱资源的利用率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Secure routing in IoT with multi-objective simulated annealing Modeling of TCM packing robot and its kinematics simulation and optimization Iterative decision-directed channel estimation for MIMO-OFDM system A systemic performance evaluation method for Residue Number System A dynamic hierarchical quotient topology model based optimal path finding algorithm in complex networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1