分散式偵測系統根據介於本地偵測器與資料融合中心之間不同的存取通道，可以分成平行與非平行兩種；本篇論文探討使用直接序列分碼多工的非平行存取通道之分散式偵測系統。在此系統下前人提出了低複雜度的兩階段融合法則，第一階段由多使用者偵測器求出各個本地判斷之估計值，第二階段使用Chair-Varshney (CV)法則融合估計值後求出決策。然而目前第二階段之CV法則忽略存取通道的錯誤率，我們因此提出考量通道錯誤率的改良式CV法則。模擬結果顯示在增加通道資訊及搭配最小化均方誤差偵測器的情況下，能有效抵抗通道間的互相干擾。為了再增加偵測效能，我們將粗略的通道資訊即通道錯誤率，由更加詳細的通道模型描述。我們把第一階段多使用者偵測器輸出的軟性評估，在忽略雜訊間的相關性下視為經過平行系統通道的輸出，所以在第二階段我們可利用平行系統下的融合法則取代CV法則。模擬結果顯示，使用多使用者偵測器中的去相關偵測器搭配平行系統下的最佳概似比法則，比改良式CV法則擁有更強健的偵測效能。

For the distributed detection systems, the channels between the local sensors and data fusion center can be classified as parallel or multiple-access channels. In this thesis, we focus on distributed detection systems that use direct-sequence code-division multiple-access signaling to send the local decisions made by the sensors to the fusion center over fading multiple-access channels. In the literature, a framework of the two-stage fusion rule was proposed. The first stage uses the multiuser detector to estimate the transmitted local decisions, followed by the second stage that performs decision fusion using the Chair-Varshney (CV) rule. However, the CV rule assumes that the channels are error-free, which is not always the case. Therefore, we propose the improved CV rule that account for the error rates of the channels in decision fusion in order to enhance the detection performance, as demonstrated by the simulation results. To further improve the detection performance, we adopt the soft outputs of the multiuser detector as the refined indications of the reliabilities of the channels, and incorporate them in decision fusion. Furthermore, when we ignore the correlations between the noises in the soft outputs of the decorrelators and the minimum mean squared error (MMSE) detectors, these soft outputs can be viewed as the outputs of the parallel channels. Therefore, we can leverage the existing fusion rules developed for the parallel systems. Simulation results show that, when we use the decorrelators together with the likelihood ratio rule, the performance is better than the improved CV rule.

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