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    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/48468


    題名: 一個在感知無線電網路中分散式的宣告校準方法;A Distributed Declaration Calibration Scheme in Cognitive Radio Networks
    作者: 黃信發;Shin-Fa Huang
    貢獻者: 資訊工程研究所
    關鍵詞: 無線感測網路;頻譜偵測;分散式演算法;感知無線電網路;Wireless Sensor Networks;spectrum sensing;distributed algorithm;Cognitive Radio Networks
    日期: 2011-07-28
    上傳時間: 2012-01-05 14:55:36 (UTC+8)
    摘要: 感知無線電網路(Cognitive Radio Networks)的概念要能夠實行,頻譜感測是一個重要的關鍵技術。感知無線電網路系統中的次要使用者(Secondaryusers, SUs),經由頻譜感測所得到的主要使用者(Primary users, PUs)是否正在使用頻譜的資訊,能夠機會式使用頻譜,然而一般而言,SU 並不能夠同時傳送資料以及作感測,因此使用頻譜機會的效率便會降低,也因為現今頻譜感測的硬 體技術尚未成熟,令感知無線電網路能夠較快實行且不降低SU 使用頻譜機會的作法是使用無線頻譜感測器網路(WSSNs)。然而在大自然中存在訊號衰弱(shadowing fading)、多重路徑(multi-path effects)等現象,使得頻譜感測的結果有可能有錯誤產生,因此在本篇論文中,我們利用偵測PU 所在的方位,能夠得知是否有頻譜感測錯誤的節點在附近,進而推演出了一個分散式的宣告校準頻譜感測結果的方法,並且調整了舊有的服務模型,使其作法更貼近現實,並且能更快實行,根據實驗結果,我們得到一個不錯的結果,相信這對未來感知無線電網路真正的實行有所幫助,也給無線頻譜感測器網路系統帶來一個不同的思維。 Cognitive Radio Networks(CRNs) will be enable to implement, spectrum sensing is a important key technology. Secondary Users(SUs) in cognitive radio are opportunistic allowed to access the spectrum when it get the information about whether Primary Users(PUs) are using the spectrum or not by sensing spectrum. In general, SUs cannot support simultaneous sensing and accessing spectrum. Therefore, the efficiency of utilizing the spectrum opportunities will be degraded. Also because spectrum sensing hardware isn’t mature yet. Using dedicated Wireless Spectrum Sensor Networks (WSSNs) is a way that can let cognitive radio faster to carry out and don’t degrade the efficiency of utilizing the spectrum opportunities. However there is shadowing, multi-path effects and other phenomenon in nature, it may cause result of spectrum sensing error. In this thesis, we exploit detecting the direction of PU, it can find out whether it has the node which has sensing error are in nearby. Furthermore deduce a Distributed Declaration Calibration Scheme to correct the spectrum sensing error and adjust the old service model, let its service model more close to reality and faster to implement. As the result of experiment, we get a good result, believing that is helpful for real cognitive radio implement. It also brings out a different thought for WSSNs.
    顯示於類別:[資訊工程研究所] 博碩士論文

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