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研究生:林育儒
研究生(外文):Yu-Lu-Lin
論文名稱:使用二進制及四進制碼應用於無線感測器網路之分散式高能源效率決策融合
論文名稱(外文):Distributed Energy-Efficient Decision Fusion using Binary and Quaternary codes in Wireless Sensor Network
指導教授:鄭文凱鄭文凱引用關係
指導教授(外文):Victor W. Cheng
學位類別:碩士
校院名稱:國立暨南國際大學
系所名稱:通訊工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:89
中文關鍵詞: 能源效率 分散式感測器網路 決策融合 錯誤更正碼 代價
外文關鍵詞:energy-efficientdistributed sensor networksdecision fusionECCcost
相關次數:
  • 被引用被引用:0
  • 點閱點閱:123
  • 評分評分:
  • 下載下載:8
  • 收藏至我的研究室書目清單書目收藏:0
現今,無線感測器網路被廣泛應用在各式各樣的環境偵測上,由於感測器的電力來源是電池,所以電池的壽命限制了感測器的工作時間,而感測器在做無線傳輸時,耗費的電力最多,因此如何節省耗電量,是一項值得探討的課題。
在論文中,我們將二進制及四進制碼分別應用於無線感測器網路中,並設計一種機制以節省能源。而在研究中我們設計出高能源效率的演算法來減少耗電量。其機制是指,將感測器設計為,當觀測值足夠信賴時才傳送資訊給融合中心;反之,感測器則不送任何資訊給融合中心,這樣不僅能夠節省能源,還能降低錯誤率。另外,我們在四進制的應用中加入錯誤更正碼,之後發現這樣也能達到節省能源及降低錯誤率的效果。
最後,我們還設計出多種類的碼在四進制的應用中,使得最後有判斷錯誤時,能夠盡量將判斷錯誤的代價壓低,以避免付出太大的代價。
Nowadays, the battery-powered wireless sensor network (WSN) is an emerging technology with a wide variety of applications. The lifetime of a sensor is limited by the power constraint. One of the major energy consumptions in WSN is spent on the data communication. Hence, the issue of power saving in WSN should be probed into.
In this thesis, binary and quaternary codes are used individually to design a mechanism to save power in WSN. A highly energy-efficient algorithm to save the expenditure in the wireless transmission energy consumption has been proposed in the research. In the proposed mechanism, each sensor transmits data to the fusion center (FC) only when its observation is reliable, or the sensor remains in a latent status which is defined ”mute”, and hence power saving is achieved. Moreover, error correcting code (ECC) is used in the quaternary hypothesis testing to save power and to decrease the error rate.
Finally, a number of codes are designed for the quaternary hypothesis testing. The simulation results indicate that the incorrect decision with high cost at FC can be significantly reduced under the proposed codes.
致謝 i
論文摘要 ii
Abstract iii
目錄 v
圖目錄 ix
表目錄 xiii
1. 緒論 1
1.1無線感測器網路 1
1.2 Distributed detection的歷史簡介 3
1.3應用於無線感測器網路上的distributed detection 3
1.4論文架構 5
2. 將binary hypothesis testing應用在WSN底下 6
2.1 Binary hypothesis之系統架構與問題陳述 6
2.2 應用在binary hypothesis底下的各種fusion rule之介紹 7
2.2.1 Optimal LR-based fusion rule 7
2.2.2 Suboptimal fusion rule 8
2.2.2.1 Two-stage Chair-Varshney fusion rule 9
2.2.2.2 Equal Gain Combining fusion rule 11
2.2.2.3 Maximum Ratio Combining fusion rule 11
2.2.2.4 MAJORITY fusion rule 11
2.3 Suboptimal fusion rule之判斷方法 12
2.4 Binary hypothesis testing的mute機制 14
2.4.1 Mute機制 14
2.4.2 Mute機制謂何 14
2.4.3 Fusion center加入mute後的判斷方法 17
2.5多種訊號處理的方法以降低miss及false alarm之模擬與結果 19
2.5.1訊號處理的方法( I ) 19
2.5.2訊號處理的方法( II ) 25
2.5.3訊號處理的方法( III ) 27
2.5.4訊號處理的方法( IV ) 29
2.5.5訊號處理的方法( V ) 31
2.5.6訊號處理的方法( VI ) 33
2.5.7在環境會變動下所做的偵測 35
2.6 Binary hypothesis testing之結論 39
3. 將quaternary hypothesis testing應用在WSN底下 41
3.1 Quaternary hypothesis之系統架構與問題陳述 41
3.2 應用在quaternary hypothesis底下的fusion rule 42
3.3 Quaternary hypothesis之感測器的兩種models 42
3.3.1 感測器之Model(I) 42
3.3.1.1 Model(I)之mute 43
3.3.2 感測器之Model(II) 44
3.3.2.1 Model(II)之mute 44
3.3.3 Model(I)與Model(II)之比較 45
3.3.4 Fusion center加入mute後之判斷方法 45
3.4 將ECC應用於quaternary hypothesis testing 47
3.5 Quaternary hypothesis testing之模擬與結果 50
3.5.1 Model(I) 50
3.5.2 Model(II) 58
3.6 Quaternary hypothesis testing之結論 61
4. 四種不同cost的hypotheses 64
4.1 Model(I)底下之模擬結果 65
4.2 Model(II)底下之模擬結果 69
5. 結論與未來展望 73
參考文獻 74
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