基於量化為單一位元之感測器觀測資料 實行具通道感知之分散式最大似然估計

無線感測網路系統為近年來十分熱門的無線通訊技術，該系統是由偵測對象、感測器裝置以及處理中心三部分所組成。本篇論文中，實際考慮受雜訊干擾之目標信號偵測，而為了節省傳輸頻寬及減少訊息傳輸時之能量消耗，每個感測器將其觀測資料量化為單一位元後，再傳送至處理中心。在過去相關文獻中，其假定的局部感測環境為各個區域的感測器所受到環境雜訊干擾之功率皆相同，但實際情況中，即便各個感測節點分佈的位置再接近，環境的雜訊功率仍然有所差異，因此，我們針對此點，進一步地考慮各個感測器所接收之環境雜訊功率皆相異。本篇論文中，感測器與處理中心間之傳輸通道為非理想通道，由於無線通訊的特性，更明確地設定通道為瑞利衰落通道。處理中心彙整感測器所傳送之觀測資料後，根據這些資訊，採用分散式最大似然估計法作為處理訊號之準則，判斷感測器所偵測之目標信號為何。而為了能使估計結果更加精準，我們藉由設計量化閾值來嘗試最小化估計誤差。在本篇論文中，模擬結果證實此組量化閾值確實使估計結果更為準確。

關鍵字

分散式估計；瑞利衰落通道；最大似然估計；無線感測網路

並列摘要

In this thesis, we study the problem of distributed estimation of an unknown deterministic parameter via wireless sensor networks (WSNs) in a noisy environment. While most recent works focused on a homogeneous sensing field, we consider the general inhomogeneous case. To conserve the bandwidth resource, each sensor observation is quantized into a one-bit message, which is then transmitted to the fusion center (FC). In our study, the communication links between sensors and the FC are imperfect and modeled as i.i.d. Rayleigh fading channels. Based on one-bit quantized observations transmitted from local sensors, the maximum-likelihood (ML) fusion rule is adopted at the FC for parameter estimation. The Cramér–Rao Lower Bound (CRLB) is derived in a closed-form. We then study the optimal local quantization threshold design via CRLB minimization. Computer simulations are used to illustrate the performance of the proposed scheme.

並列關鍵字

Distributed estimation ； quantization ； Rayleigh fading channels ； maximum-likelihood estimation ； Cramér–Rao Lower Bound ； wireless sensor networks

參考文獻

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基於量化為單一位元之感測器觀測資料實行具通道感知之分散式最大似然估計

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