適用於多天線系統之結合型並行調適性濾波器演算法

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姓名

楊長迪(Chang-Di Yang) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

適用於多天線系統之結合型並行調適性濾波器演算法
(The combination Concurrent Adaptive Filter algorithm for multi-antenna system)

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至系統瀏覽論文 ( 永不開放)

摘要(中)

在本篇論文中，我們提出了一個適用於並行調適性濾波器的演算法MBER+CC，首先介紹CAF的特性與優點，之後分別求出Channel Capacity與MBER的權重更新，接下來利用CAF的特性結合這兩種演算法之權重，得出新的演算法MBER+CC之權重。最後在模擬的結果中，我們也會呈現出MBER+CC演算法確實擁有比傳統調適性濾波器還要更好的效能。與原本的MBER與Channel Capacity演算法相比，MBER+CC演算法確實擁有較好的效能，並且消除了這兩種調適性演算法的缺點。

摘要(英)

In this paper, we propose a Concurrent Adaptive Filter algorithm MBER + CC. We first introduced the features and benefits of CAF. Then, separately, we find weight update of Channel Capacity and MBER algorithm. Then use the characteristics of CAF, to combine these two weight of algorithms, and get new weight of MBER + CC algorithms. In the simulation results, we show MBER + CC algorithms do have even better performance than the classical Adaptive Filter.
Compared with the original algorithm MBER and Channel Capacity, MBER + CC algorithms do have better performance, and eliminates the disadvantages of these two adaptive filter algorithm.

關鍵字(中)

★ 並行調適性濾波器演算法

關鍵字(英)

★ Concurrent Adaptive Filter algorithm

論文目次

目錄
摘要 i
Abstract ii
目錄 iii
圖目錄 v
表目錄 vii
第一章緒論 (Introduction) 1
第二章智慧型天線 (Smart Antenna) 3
2-1等距線性天線陣列通道模型(ULA) 5
2-2波束成型演算法(Adaptive Filter for Beamformer) 7
2-2-1 MMSE 最小均方誤差法 9
2-2-2 MBER 最小位元錯誤率法 12
2-2-3 Channel Capacity 通道容量 16
第三章 24
並行調適性濾器演算法（Concurrent Adaptive Filtering Algorithm） 24
3-1 系統模型 25
3-2 MBER+ Channel Capacity 25
3-2-1 Channel Capacity之權重 25
3-2-2 MBER之權重 27
第四章模擬結果 (Simulation results) 29
4-1 系統模擬架構(Simulation System) 29
4-2 非動態環境(Non-Dynamic Environment) 30
收斂速度比較(Convergence-Rate Comparison) 30
4-3 動態環境(Dynamic Environment) 46
收斂速度比較(Convergence-Rate Comparison) 46
結論 (Conclusion) 51
參考文獻 (Reference) 52

參考文獻

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指導教授

賀嘉律(Chia-Lu Ho)

審核日期

2015-7-21

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