台灣留學生出席國際會議補助

2009年4月21日 星期二

Decision Fusion in Sensor Networks for Spectrum Sensing based on Likelihood Ratio Tests

 論文發表人:鍾偉和(加州大學洛杉磯分校電機工程研究所博士班)

 

http://spie.org/

 

近年來由一定數量的偵測器所形成之偵測器網路已有廣泛的應用,其中一個重要的應用就是經由偵測器的共同決策來增加訊號偵測的準確度。在感知無線電的應用中,訊號偵測的準確度相當重要,在這篇論文中,我們研究利用偵測器網路共同決策來作為感知無線電頻譜偵測的方法,我們的研究架構是利用可能性比率的方式。在可能性比率的架構中,每一個偵測器作各自獨立的偵測,這些獨立的偵測結果再傳送到中央決策點進行最後決策,經由融合多數的獨立決策的方式,最後決策將會有較高的準確度。我們提出一個偵測機率低標的準則來作為傳統尼曼皮爾森準則之外的一個決策準則,在偵測機率低標準則裡,偵測器維持偵測機率在一定水準之上,追求最小的誤警報率。在感知無線電中,偵測機率低標準則可以限制頻譜衝突的機率在一定水準之下。在這篇論文中,我們也提供演算法可以計算出在決策中心的決策規則、偵測率、及誤警報率。在無線電訊號的偵測中,無線通道常常影響偵測的準確度,我們把無線通道的特性考慮進演算法中,經由考慮無線通道的特性,訊號偵測的準確度可以增加。我們並在文中提供模擬的結果來驗證所提出的演算法。

 

Sensor networks have been shown to be useful in diverse applications. One of the important applications is the collaborative detection based on multiple sensors to increase the detection performance. To exploit the spectrum vacancies in cognitive radios, we consider the collaborative spectrum sensing by sensor networks in the likelihood ratio test (LRT) frameworks. In the LRT, the sensors make individual decisions. These individual decisions are then transmitted to the fusion center to make the final decision, which provides better detection accuracy than the individual sensor decisions. We provide the lowered-bounded probability of detection (LBPD) criterion as an alternative criterion to the conventional Neyman-Pearson (NP) criterion. In the LBPD criterion, the detector pursues the minimization of the probability of false alarm while maintaining the probability of detection above the pre-defined value. In cognitive radios, the LBPD criterion limits the probabilities of channel conflicts to the primary users. Under the NP and LBPD criteria, we provide explicit algorithms to solve the LRT fusion rules, the probability of false alarm, and the probability of detection for the fusion center. The fusion rules generated by the algorithms are optimal under the specified criteria. In the spectrum sensing, the fading channels influence the detection accuracies. We investigate the single-sensor detection and collaborative detections of multiple sensors under various fading channels, and derive testing statistics of the LRT with known fading statistics.