基于改进能量检测器的联合滤波和加权融合频谱传感

S. Nallagonda, Mahendar Gajula, Sanjay Dhar Roy, S. Kundu
{"title":"基于改进能量检测器的联合滤波和加权融合频谱传感","authors":"S. Nallagonda, Mahendar Gajula, Sanjay Dhar Roy, S. Kundu","doi":"10.1109/ICCCT2.2014.7066710","DOIUrl":null,"url":null,"abstract":"In the present article, the cooperative spectrum sensing with a weighted fusion (WCSS) scheme has been analyzed in Rayleigh fading. Cognitive radio (CR) uses an improved energy detector (IED) with several antennas. Antenna selection diversity combining (SC) is performed at each CR on the basis of the values of decision statistics measured from different antennas at IED. Every CR takes 1-bit decision regarding primary user (PU) and sends its decision to fusion center (FC) with binary phase shift keying (BPSK) signaling if FC selects that CR to send. The FC estimates weight factors of selected CRs with the help of a profile of average SNRs and incorporated with decisions of each selected CR. The missed detection performance is evaluated for different values of improved detector parameter with different number of antennas, average SNRs of sensing (S) and reporting (R) channels. WCSS with censoring performance is also analyzed for perfect and imperfect estimation cases. Combined censoring and weighted fusion significantly improves the spectrum sensing performance.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Combined censoring and weighted fusion based spectrum sensing with improved energy detector\",\"authors\":\"S. Nallagonda, Mahendar Gajula, Sanjay Dhar Roy, S. Kundu\",\"doi\":\"10.1109/ICCCT2.2014.7066710\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the present article, the cooperative spectrum sensing with a weighted fusion (WCSS) scheme has been analyzed in Rayleigh fading. Cognitive radio (CR) uses an improved energy detector (IED) with several antennas. Antenna selection diversity combining (SC) is performed at each CR on the basis of the values of decision statistics measured from different antennas at IED. Every CR takes 1-bit decision regarding primary user (PU) and sends its decision to fusion center (FC) with binary phase shift keying (BPSK) signaling if FC selects that CR to send. The FC estimates weight factors of selected CRs with the help of a profile of average SNRs and incorporated with decisions of each selected CR. The missed detection performance is evaluated for different values of improved detector parameter with different number of antennas, average SNRs of sensing (S) and reporting (R) channels. WCSS with censoring performance is also analyzed for perfect and imperfect estimation cases. Combined censoring and weighted fusion significantly improves the spectrum sensing performance.\",\"PeriodicalId\":6860,\"journal\":{\"name\":\"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)\",\"volume\":\"1 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCT2.2014.7066710\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCT2.2014.7066710","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文分析了基于加权融合的瑞利衰落协同频谱感知方案。认知无线电(CR)使用一种改进的带有多个天线的能量探测器(IED)。天线选择分集组合(Antenna selection diversity combine, SC)是基于IED中不同天线的决策统计量进行的。每个CR对主用户(PU)进行1位决策,如果FC选择发送该CR,则通过二进制相移键控(BPSK)信令将其决策发送给融合中心(FC)。FC利用平均信噪比曲线估计所选CR的权重因子,并结合每个所选CR的决策,对不同天线数、感知(S)和报告(R)通道的平均信噪比下改进的检测器参数的不同值进行漏检性能评估。同时分析了具有过滤性能的WCSS的完美估计和不完美估计情况。结合滤波和加权融合,显著提高了频谱感知性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Combined censoring and weighted fusion based spectrum sensing with improved energy detector
In the present article, the cooperative spectrum sensing with a weighted fusion (WCSS) scheme has been analyzed in Rayleigh fading. Cognitive radio (CR) uses an improved energy detector (IED) with several antennas. Antenna selection diversity combining (SC) is performed at each CR on the basis of the values of decision statistics measured from different antennas at IED. Every CR takes 1-bit decision regarding primary user (PU) and sends its decision to fusion center (FC) with binary phase shift keying (BPSK) signaling if FC selects that CR to send. The FC estimates weight factors of selected CRs with the help of a profile of average SNRs and incorporated with decisions of each selected CR. The missed detection performance is evaluated for different values of improved detector parameter with different number of antennas, average SNRs of sensing (S) and reporting (R) channels. WCSS with censoring performance is also analyzed for perfect and imperfect estimation cases. Combined censoring and weighted fusion significantly improves the spectrum sensing performance.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Novel Image Watermarking Scheme Using LU Decomposition Streaming Algorithm for Submodular Cover Problem Under Noise Hand part segmentations in hand mask of egocentric images using Distance Transformation Map and SVM Classifier Multiple Imputation by Generative Adversarial Networks for Classification with Incomplete Data MC-OCR Challenge 2021: Simple approach for receipt information extraction and quality evaluation
×
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