臺灣博碩士論文加值系統

於本論文中, 我們發展出一些高效能之軟性決策資訊協助多使用者偵測
器解調, 運用在群組式的多重輸入多重輸出的直序碼多工調變系統下。
為提升階層式時間-空間多使用者偵測器的效能, 根據最小均方誤差法則,
我們提出使用多級式軟性決策迴授最小均方誤差法, 並且在接收端加了一個
的軟性迴授因子, 以加強輔助偵測之用。我們所提出的方法比傳統階層式時
間-空間多使用者偵測器有更佳的系統效能, 但其缺點為該方法計算複雜度偏
高,因此我們又提出了一種可降低複雜度之多級軟性階層決策干擾消除法, 以
降低運算複雜度與處理時間。該方法是先把其他群的干擾予以估測後, 並從接
收訊號中去除, 扣除掉其他群的干擾, 使其複雜度降低。
最後, 我們對發展之演算法, 進行電腦模擬與效能分析, 而實驗的結果也
驗証了本文所提的多使用者解調器, 確實能提供較低的複雜度與高效能的解
調的能力。

This thesis presents two novel group layered space-time multiuser detectors
(MUDs) with the assistance of soft information for the uplink of multiple-input
multiple output (MIMO) code division multiple access (CDMA) systems, in which
the transmit antennas are divided into several virtual groups with the transmit
antennas in each group being assigned a unique signature sequence.
To effectively combat the interference, a multistage soft MMSE MUD is first
addressed, which iteratively determine the MUD by incorporating the soft group
information fed back from the previous iteration. Despite its high performance,
the aforementioned MUD also calls for enormous amount of computations. To
alleviate this setback, we also consider another MUD, which reconstructs the interference
induced by other groups and then removes it from the received signal
before proceeding the detection so as to lower the computational load. Conducted
simulations demonstrate that both of the developed MUDs can offer significant
performance gain compared with pervious works in various scenarios and that the
second MUD considered is slightly inferior but with substantially reduced complexity.

第一章緒論1
1.1 引言. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 研究動機與目的. . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3 內容章節概述. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
第二章背景回顧7
2.1 訊號模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.1 直序分碼多工調變存取資料模型. . . . . . . . . . . . . . 8
2.1.2 多重輸入多重輸出直序分碼多工調變系統資料模型. . . . 10
2.2 多使用者偵測器. . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2.1 最佳化接收器. . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2.2 次佳化線性接收器. . . . . . . . . . . . . . . . . . . . . . . 15
2.2.3 干擾消除. . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.2.4 結語. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
第三章多級式軟性決策多使用者偵測23
3.1 相關背景的回顧. . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2 多級式軟性決策迴授最小均方誤差法. . . . . . . . . . . . . . . . 26
3.3 電腦模擬結果與討論. . . . . . . . . . . . . . . . . . . . . . . . . 32
3.4 運算複雜度分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.5 結語. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
第四章軟性決策低複雜度干擾消除法42
4.1 多級式軟性決策干擾消除法. . . . . . . . . . . . . . . . . . . . . 42
4.2 電腦模擬結果與討論. . . . . . . . . . . . . . . . . . . . . . . . . 45
4.3 效能與運算複雜度分析. . . . . . . . . . . . . . . . . . . . . . . . 49
4.4 結語. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
第五章結論及未來展望59
5.1 結論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
5.2 未來展望. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
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