本文主要是介紹一種應用於CDMA多用戶檢測的技術(multi-user detection scheme)，利用最小均方演算法(Least-Mean-Square, LMS)及遞迴最小平方演算法(Recursive Least-Squares, RLS)來取代去相關檢測器(Decorrelating Detector, DD)及最小均方誤差(Minimum Mean-Square Error, MMSE)檢測器，這兩種線性多用戶檢測器中的反矩陣，我們主要是利用Wiener濾波器在LMS及RLS下的適應性方式，套用到這兩種線性多用戶檢測器中，以達到減少檢測的計算量。
在本論文中主要是先根據Wiener濾波器，建構出去相關橫向濾波器，再以這個濾波器為基礎，加上LMS及RLS這兩種不同的演算法於此濾波器。我們還考慮到實際通道中存在的多重路徑效應，假設已知可分辨的多重路徑數目，並且也知道每一個路徑的衰減增益(path gain)，經由通道多路徑的模擬，以克服多路徑效應的影響，由模擬曲線，可以證明了這樣的改善能有效的改善系統在遭遇多路徑效應時的性能。
最後，再根據比較去相關檢測器與MMSE檢測器的不同，修改去相關橫向濾波器中的輸入部份，以達到MMSE檢測器的要求，這樣的改變經由實驗模擬，可以得到即使使用者數目很多，也不會發生如去相關檢測器般加強了雜訊項。

The well-known code division multiple access (CDMA) decorrelating detector (DD) and minimum mean-square error (MMSE) detector use a bank of correlators, followed by the inverse of the matrix operation to eliminate the multiple access interference (MAI). However, the operation for the inverse of the matrix involves a great deal of computation, especially when the users’ number is large. Therefore, in this thesis, we propose some recursive methods, the least-mean-square (LMS) algorithm and the recursive least-squares (RLS) algorithm, to detect users’ signals adaptively. We make use of the analogy between a traditional Winner filter and the decorrelating detector to construct adaptive implementation schemes of the decorrelating detector and MMSE detector, called decorrelating transversal filter and MMSE transversal filter, respectively. We applied both LMS algorithm and RLS algorithm to the decorrelating transversal filter and MMSE transversal filter, just as the ways to apply the LMS algorithm and RLS algorithm to the Winner filters. With the proposed schemes, we can greatly reduce the computational complexity of a CDMA multi-user detector while maintaining an acceptable performance.

第一章 導論
1-1 研究動機
1-2 論文架構

第二章 CDMA多用戶線性檢測器及Wiener濾波器
2-1 概要
2-2 CDMA去相關檢測器 (Decorrelating Detector, DD)
2-3 CDMA最小均方誤差檢測器 (MMSE Detector)
2-4 Wiener濾波器
2-5 去相關橫向濾波器

第三章 適應性最小均方演算法多用戶檢測器
3-1 最小陡坡演算法 (Steepest Descent Algorithm)
3-2 最小均方演算法 (Least-Mean-Square Algorithm, LMS)
3-3 同步無多路徑通道下，使用LMS演算法於去相關橫向濾波器
3-4 同步無多路徑通道下，適應性LMS去相關橫向濾波器分析
3-5 同步多路徑通道下，使用LMS演算法於去相關橫向濾波器
3-6 同步無多路徑通道下，使用LMS演算法於MMSE橫向濾波器

第四章 適應性遞迴最小平方演算法多用戶檢測器
4-1 遞迴最小平方演算法 (Recursive Least-Squares, RLS)
4-2 同步無多路徑通道下，使用RLS演算法於去相關橫向濾波器
4-3 同步多路徑通道下，使用RLS演算法於去相關橫向濾波器
4-4 同步無多路徑通道下，使用RLS演算法於MMSE橫向濾波器

第五章 結論
5-1 結論
5-2 適應性LMS去相關檢測器與並行消去干擾檢測器之比較

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