臺灣博碩士論文加值系統

多使用者解調器在近代通訊研究中扮演著重要的角色，但隨著天線陣列的加入，多使用者解調器的複雜度更顯重要。本論文嘗試以消息理論準則為基礎，在TDMA系統中發展低複雜度的多使用者解調器，以期得到與CDMA相當的頻道使用率。
本論文第一個論述為我們在低頻率重複使用率下發展一低複雜度多使用者解調器。因同頻道干擾源在TDMA系統中之平均功率小於主要使用者功率，我們利用已估測的通道，根據同頻道干擾源每階的功率大小，保留較大功率階，而捨去較小功率者，以最小均方差準則設計低複雜度多使用者解調器。此外，我們亦針對此低複雜度多使用者解調器推導其位元錯誤率以及分析其計算複雜度。效能分析與計算機模擬結果驗證了此演算法能提供和全複雜度多使用者解調器近似的效能，但其所需的計算量卻大幅降低。
第二個論述在於以消息理論準則為基礎決定該低複雜度多使用者解調器所需之有效通道長度。我們首先利用已發展之消息理論準則決定有效通道長度，然後提出修改消息理論準則以將接收信號投影至同頻道干擾源空間與雜訊空間，有效地決定同頻道干擾源之通道長度，並應用於設計低複雜度多使用者解調器時可保留主要使用者的訊息。此外，我們亦針對此修改消息理論準則分析其一致性，並且與其它相關研究做比較與討論。基於以消息理論準則為基礎決定有效通道長度，模擬所得之效能相似於使用全通道長度之多使用者解調器。
最後，我們將該設計之低複雜度多使用者解調器結合動態通道分配技術，利用兩者之間補償的特性，以期得到更高的網路容量。我們使用距離與角度限制條件設計一新的動態通道分配方法以決定同一通道的合法使用者。利用此動態通道分配技術，同一通道內的使用者在時間與空間上更不具有相關性，故多使用者解調器可使用較少的同頻道干擾源訊息而得到相近的效能，如此可更進一步降低計算複雜度。模擬結果驗證了此結合演算法確實在較高的網路容量下得到較低的複雜度，而且也得到可接受的效能。

In this dissertation, a low complexity antenna array-assisted multiuser detection (MUD) which is based on the information theoretic criteria is proposed to detect the desired
signal in TDMA systems. The contributions of this dissertation
include the followings.
First, a low complexity antenna array-assisted minimum mean-squared error (MMSE) MUD is addressed, which utilizes only
partial information of the co-channel interferences (CCIs) in the demodulation process. In light of the fact that the power of the CCIs is lower than that of the desired user as the CCIs are out-of-cell in TDMA, the proposed approach truncates the channel length of the CCIs adaptively based on the power of the channel taps of the CCIs. As the truncated channel taps only account for negligible information of the CCIs, the performance does not substantially degrade. Moreover, the analytic expressions of the bit error rate (BER) performance for both of the full complexity and the proposed low complexity MMSE MUD are derived. Simulation results show that the simulations and the analytic results agree well in various scenarios, and that the performance remains close even if we truncate $60\%$ CCI channel length.
Second, information theoretic criteria, which include the Akaike information theoretic criterion (AIC) and Rissanen's minimum distance length (MDL) criterion, are employed to form a theoretic foundation to determine the effective CCI channel length in the developed MUD. Two information theoretic approaches are considered. The first one is a direct extension of the previous works. Aiming at keeping the information of the desired user intact in the truncation, we propose modified information theoretic criteria, which first project the received signals onto the CCIs subspace and the noise subspace before the embarkation of the information theoretic analysis. To assess the statistical behavior of the proposed criteria, the consistency property is also investigated. The built simulations show that the developed MUD with the effective CCI channel length determined by the information theoretic criteria yields indistinguishable performance as the full complexity counterpart.
Finally, to enhance the spectrum efficiency, we address a simple, yet effective dynamic channel assignment (DCA), which employs the angle constraints and distance constraints as the criteria to assign frequency bands. With a combination of the developed low complexity MUD and DCA, which are compensatory to each other, we can truncate more redundant information of the CCIs and thus achieve lower complexity, while still maintaining acceptable BER performance.

1 INTRODUCTION
1.1 Background and Related Works ………………………………2
1.2 Outline of Thesis ……………………………………………6
2 WIRELESS COMMUNICATION CHANNEL MODEL 10
2.1 Wireless Propagation channel ……………………………10
2.1.1 Path Loss ………………………………………………………11
2.1.2 Fading Characteristics ……………………………………11
2.1.3 Multipath Propagation ………………………………………13
2.2 Space-Time Signal Processing ……………………………15
2.2.1 Antenna Array-Based Receiver ……………………………15
2.2.2 Pulse Shaping Function ……………………………………17
2.3 Discrete Space-Time Signal Channel Model ……………20
2.3.1 Space-Time Signal Channel Model …………………………20
2.3.2 Space-Time Signal-plus-Interference Channel Model …24
2.4 GSM system ……………………………………………………27
2.5 Simulation Scenarios ………………………………………28
2.6 Conclusions ……………………………………………………30
3 LOW COMPLEXITY ANTENNA ARRAY-ASSISTED MULTIUSER DTECTION 31
3.1 Full Complexity MMSE Multiuser Detection ……………31
3.2 Low Complexity MMSE Multiuser Detection with Partial CCIs Information …………………………………………………………35
3.3 Performance Analysis of the MMSE Multiuser Detection……………………………………………………………………39
3.3.1 Performance Analysis of the Full Complexity MMSE Multiuser Detection ………………………………………………………39
3.3.2 Performance Analysis of the Low Complexity MMSE Multiuser Detection with Partial CCIs ………………………………41
3.3.3 Computational Complexity …………………………………44
3.4 Experiments and Discussions ………………………………44
3.5 Conclusions ……………………………………………………48
4 INFORMATION THEORETIC CRITERIA-BASED MULTIUSER
DETECTION 49
4.1 Information Theoretic Criteria …………………………51
4.2 Information Theoretic Criteria Algorithm ……………53
4.2.1 Information Theoretic Criteria Algorithm ……………54
4.2.2 Consistency Analysis ………………………………………59
4.2.3 Comparisons and Discussions ………………………………61
4.3 Simulations Results …………………………………………66
4.4 Conclusions ……………………………………………………71
5 LOW COMPLEXITY MULTIUSER DETECTION WITH DYNAMIC CHANNEL ASSIGNMENT 74
5.1 Cellular Network Model ……………………………………74
5.2 Introduction of Channel Assignment ……………………74
5.3 Dynamic Channel Assignment ………………………………77
5.4 Performance Analysis of the Dynamic Channel Assignment …………………………………………………………………81
5.5 Combination of the MMSE MUD and DCA ……………………83
5.6 Simulations and Discussions ………………………………85
5.7 Conclusions ……………………………………………………98
6 CONCLUSIONS 100
REFERENCE 104
Appendix Channel Stacking Strategy 110

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