臺灣博碩士論文加值系統

盲蔽反旋捲﹝等化﹞是一種訊號處理的程序，其目的在於僅使用未知線性非時變(LTI)通道的輸出量測資料來還原已被此通道變形的原始來源訊號。對於來源訊號是非高斯分佈且量測雜訊是高斯分佈的情況，一類使用兩個高階統計量(cumulants)的反濾波器準則已經被Wiggins、Donoho、Shalvi與Weinstein、Tugnait、祁與吳等人提出，並用於非最小相位(nonminimum-phase)線性非時變通道的盲蔽反旋捲處理。此類反濾波器準則的等化能力在訊號雜訊比(SNR)為無窮大以及通道沒有零點在單位圓上的兩個假設下已經被證明，但是相關之最佳反旋捲濾波器﹝反濾波器﹞的封閉式(closed-form)解答則至今仍然未知。
本論文主要是針對有限之訊號雜訊比以及允許通道可以有零點在單位圓上的情況下來分析此類反濾波器準則的性能。所得到的分析結果包括一些明顯的反旋捲濾波器之特性、此反旋捲濾波器與眾所皆知的非盲蔽式最小平均平方誤差(MMSE)等化器的關係以及用於求得理論上之反旋捲濾波器的一個計算上很有效率的疊代式演算法則。此外，這些分析結果更進一步地引導出一種嶄新的不易受雜訊影響之盲蔽式通道估計方法。
在另一方面，本論文也包括了與此類反濾波器準則非常相關之Shalvi及Weinstein的疊代式超指數(super-exponential)演算法則之性能及收斂速度改進成果。

Blind deconvolution (equalization) is a signal processing procedure to restore a source signal, distorted by an unknown linear time-invariant (LTI) channel, from channel''s output measurements. A class of inverse filter criteria using two cumulants has been proposed by Wiggins, Donoho, Shalvi and Weinstein, Tugnait, and Chi and Wu for blind deconvolution of nonminimum-phase LTI channels when source signal is non-Gaussian and measurement noise is Gaussian. The equalization capability of the class of inverse filter criteria was proved, based on the assumptions of infinite signal-to-noise ratio (SNR) and channels without zeros on the unit circle, but closed-form solutions for the optimum deconvolution filter (inverse filter) have not been found so far.
This thesis analyzes the performance of the class of inverse filter criteria for finite SNR with channels allowed to have zeros on the unit circle. The analytic results include several noticeable characteristics of the associated deconvolution filter, a connection of the deconvolution filter with the well-known nonblind minimum mean square error (MMSE) equalizer, and a computationally efficient iterative algorithm for obtaining the theoretical deconvolution filter. Moreover, the analytic results further lead to a novel noise-insensitive approach to blind channel estimation.
On the other hand, highly related to the class of inverse filter criteria, the Shalvi and Weinstein''s iterative super-exponential algorithm is improved in performance as well as convergence rate.

COVER
CHINESE ABSTRACT
ABSTRACT
ACKNOWLEDGMENTS
CONTENTS
1 INTRODUCTION
2 REVIEW OF THE CUMULANT BASED INVERSE FILTERING APPROACH
2.1 MODEL ASSUMPTIONS AND PROBLEM STATEMENT
2.2 CUMULANT BASED INVERSE FILTER CRITERIA
3 PERFORMANCE ANSLYSIS I: CHANNELS WITHOUT ZEROS ON THE UNIT CIRCLE
3.1 MODEL ASSUMPTIONS AND REVIEW OF THE MMSE EQUALIZER
3.2 ANALYSIS OF THE BEHAVIOR OF THE DECONVOLUTION FILTER
3.3 ANALYSIS OF THE SNR IMPROVEMENT OR DEGRADATION AFTER DECONVOLUTION
3.4 SIMULATION AND CALCULATION RESULTS
3.5 SUMMARY AND DISCUSSIONS
APPENDIX
4 PERFORMANCE ANALYSIS II: CHANNELS WITH ZEROS ON THE UNIT CIRCLE
4.1 MODEL ASSUMPTIONS AND A FURTHER PROPERTY OF THE MMSE EQUALIZER
4.2 ANALYTIC RESULTS
4.3 COMPUTER SIMULATION
4.4 SUMMARY
APPENDIX
5 BLIND CHANNEL ESTIMATION
5.1 NOISE-INSENSITIVE APPROACH TO BLIND CHANNEL ESTIMATION
5.2 COMPUTER SIMULATION
5.3 SUMMARY
6 IMPROVEMENTS ON SUPER-EXPONENTIAL ALGORITHM
6.1 REVIEW OF THE SUPER-EXPONENTIAL ALGORITHM
6.2 LATTICE SUPER-EXPONENTIAL ALGORITHM
6.3 TWO-STEP LATTICE SUPER-EXPONENTIAL ALGORITHM
6.4 SIMULATION RESULTS
6.5 SUMMARY
APPENDIX
7 CONCLUSIONS AND FUTURE RESEARCH
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