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基于無線指紋數(shù)據(jù)庫的認知無線電頻譜感知
2021年電子技術應用第7期
顏廷秋,申 濱,王 欣
重慶郵電大學 通信與信息工程學院,重慶400065
摘要: 提出了一種基于無線指紋數(shù)據(jù)庫的頻譜感知方案。首先,在蜂窩認知無線電網(wǎng)絡(Cell Cognitive Radio Network,CCRN)覆蓋的目標地理區(qū)域內,次用戶設備(Secondary User Equipment,SUE)收集大量頻譜觀測數(shù)據(jù),基于各種機器學習算法對頻譜觀測數(shù)據(jù)進行處理得到授權頻譜上主用戶發(fā)射機(Primary User Transmit,PUT)的傳輸模式;隨后,在PUT不同的傳輸模式下劃分地理位置區(qū)域,采用基于空間距離計算的方法獲取網(wǎng)格標簽,建立無線指紋數(shù)據(jù)庫;最后,有感知需求的次用戶設備(Secondary User Equipment,SUE)根據(jù)接收到的基站(Base Station,BS)參考信號的到達時間(Time Of Arrival,TOA)估計值來獲取其無線指紋,然后與無線指紋數(shù)據(jù)庫(Wireless FingerPrint Database,WFPD)中的無線指紋(Wireless FingerPrint,WFP)進行匹配確定其地理位置,并由此確定授權頻段的接入標簽。仿真結果表明,本方案方案在減少對主用戶干擾的前提下,增加了授權頻譜的接入機會。
中圖分類號: TN92
文獻標識碼: A
DOI:10.16157/j.issn.0258-7998.201235
中文引用格式: 顏廷秋,申濱,王欣. 基于無線指紋數(shù)據(jù)庫的認知無線電頻譜感知[J].電子技術應用,2021,47(7):69-73.
英文引用格式: Yan Tingqiu,Shen Bin,Wang Xin. Wireless fingerprint database based spectrum sensing in cognitive radio network[J]. Application of Electronic Technique,2021,47(7):69-73.
Wireless fingerprint database based spectrum sensing in cognitive radio network
Yan Tingqiu,Shen Bin,Wang Xin
School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications, Chongqing 400065,China
Abstract: This paper proposes a spectrum sensing scheme based on wireless fingerprint database. Firstly, in the target geographic area covered by the cellular cognitive radio network(CCRN), the secondary user equipment(SUE) collects a large number of spectrum observation data, and processes the spectrum observation data based on various machine learning algorithms to obtain the transmission mode of primary user transmit(PUT) on the authorized spectrum. Then, in the different transmission modes of put, the geographic location area is divided, and the grid label is obtained based on the spatial distance calculation method, and the wireless fingerprint database is established. Finally, the secondary user equipment(SUE) with sensing needs obtains its wireless fingerprint according to the time of arrival(TOA) estimation of the base station(BS) reference signal, and then compares it with the wireless fingerprint in the wireless fingerprint database(WFPD) to determine its geographical location, and thus to determine the access tag of authorized frequency band. Simulations verify that the proposed scheme increases the spectrum access opportunity under the premise of minimizing the interference to the primary user.
Key words : spectrum sensing;wireless fingerprint database(WFPD);machine learning;cell cognitive radio

0 引言

    傳統(tǒng)頻譜感知算法存在很大的局限性[1-4],而當前機器學習算法在頻譜感知中廣泛應用[5-6]?;诖爽F(xiàn)狀,本文提出了基于無線指紋數(shù)據(jù)庫的頻譜感知方案。本方案中,首先利用機器學習的方法對CCRN區(qū)域內收集的頻譜觀測數(shù)據(jù)進行處理,從而獲取該區(qū)域內的PUT聯(lián)合傳輸模式信息;然后在PUT聯(lián)合傳輸模式確定且PUT位置已知的情況下,以活躍PUT為中心劃分地理區(qū)域,基于空間距離的算法確定不同網(wǎng)格的頻譜可用性標簽;最后將PUT的聯(lián)合傳輸模式信息和頻譜可用性信息存儲在數(shù)據(jù)庫中。有感知需求的SUE可以借助存儲在無線指紋數(shù)據(jù)庫中的信息和數(shù)據(jù),輕松地作出頻譜決策。無線指紋數(shù)據(jù)庫的方案實現(xiàn)了認知無線電中頻譜感知即插即用的需求,其劃分地理區(qū)域的方式使得SUE可以獲得更多的潛在頻譜接入機會。仿真結果顯示,本方案能有效地滿足頻譜感知的需求。




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作者信息:

顏廷秋,申  濱,王  欣

(重慶郵電大學 通信與信息工程學院,重慶400065)




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