記
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6771
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號
狀
NC094FJU00428007
態
助
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查
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索
書
號
學
校
輔仁大學
名
稱
系
所
電子工程學系
名
稱
舊
系
所
名
稱
學
492506056
號
研
究
生 沈煥鈞
(
中
)
研
究
Huan-Chun Shen
生
(
英
)
論
文
名
稱 新群體盲目多使用者偵測器在多通道路徑的直接序列分碼多重接取系統
(
中
)
論
文
名
稱 A Novel Group Blind Multiuser Detection for DS-CDMA Systems with Multipaths
(
英
)
其
他
題
名
指
導
教
授 余金郎
(
中
)
指
導
教
授 Jung-Lang Yu
(
英
)
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學 94
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出
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文 英文
別
關
鍵
字 群體 偵測器 偵側器 複雜度 使用者 缺點 直接序列分碼多重接取 CDMA
(
中
)
關
鍵
字 Group DS-CDMA Group Blind Multiuser Detection
(
英
)
摘
要
(
中
)
第三代行動通訊立基於分碼多工存取(CDMA)的系統上，因為CDMA的系統可以提供
比分時多工存取(TDMA)和分頻多工存取(FDMA)較好的能力。但在CDMA的系統中
虛擬序列不能完全的有正交特性在多路逕的環境底下，訊號在接收端就很難被偵測出
來。傳統盲目估測的偵側器藉由已知需被偵測出使用者的展頻序列而發展出來的。如
果接收端已經知道群體使用者的展頻序列，相對應的矩正將可以被估測出來而且群體
盲目偵測器可以立用額外的群體的限制被發展出。群體盲目多使用者偵測器已經發展
在上傳和下傳的CDMA系統. 最早的群體盲目偵測器利用群體限制發展出，但這樣的
群體限制只能利用已知群體使用者的展頻序列和相關向量而取得。由此缺點，改進的
群體盲目線性偵測器利用訊號之間的相關訊息去產生群體限制而且只要使用需被偵測
出使用者的相關向量。 在這篇論文,我們發現這個改進過的限制有些矛盾在取樣的情
形下。而且強化後的限制為了改善性能被發表出。考慮到實際的操作上，強化偵測器
的複雜度可以利用轉換線性偵測器被減少而且也簡化了接收端的偵測器。模擬結果會
證明強化偵測器和轉換偵測器比之前的偵測器有更好的性能。
摘
要
(
英
)
The 3rd generation mobile communication will base on code-division multiple-access
(CDMA) system, because CDMA systems can provide more capacity than time-division
multiple access (TDMA) and frequency-division multiple access (FDMA). But in CDMA
systems the pseudo-noise sequences are not exactly orthogonal in multipath environments;
signals can not be detected in the receiver. The conventional blind mutiuser detectors are
developed by only knowing the spreading sequence of the desired user. If the receiver has
known the spreading sequences of a group of users, the corresponding signature matrix can
be estimated and the group-blind detectors can be developed by using additional group
constraints. Group Blind mutiuser detectors had been developed in uplink and downlink
CDMA systems. The first group blind detectors are developed by adding the group
constraints, but these group constraints are derived only if the spreading sequences and thus
the signature vectors of a group of users are known. In light of this disadvantage, an
improved group-blind linear detector use the correlation information between consecutively
received signals to generate the corresponding group constraint and only use the signature
vectors of the desired user. In this paper, we find the contradiction of these improved
constraints in the finite sample scenario .Then the enhanced constraints were proposed for
improving performance gain, and construct enhanced detectors. Considering the real-time
implementation, the computational complexity of the enhanced detectors can be reduced by
using a transformation-based linear detector and simplify the detectors in the receiver.
Simulation results demonstrate Enhanced detectors and transformation detectors have better
performance.
論
文
目
次
Contents Abstract ( in Chinese)…………………………………………………………i
Abstract ………………………………………………………………………………ii
Acknowledgement……………………………………………………………………iii
Contents……………………………………………………………………………………iv
List of figures…………………………………………………………………………vi 1.
Introduction…………………………………………………………1 1.1 Multiple Access
Techniques…………………………………………………1 1.2 Overview of
CDMA…………………………………………………………2 1.3 A Motive of
Research………………………………………………………3 1.4 Group-Blind Multiuser
Detection……………………………………………4 1.5 Outline of
Thesis……………………………………………………………5 2. Basic
Fundamentals………………………………………………………7 2.1 Basic Fundament of
DS-CDMA……………………………………………7 2.2 A Cellular CDMA
system………………………………………………10 2.3 The MAI and Near Far
Problem……………………………………………12 3. Review of group-blind multiuser
detectors and blind channel Estimation……………………………………14 3.1 Review of
Group-Blind Multiuser Detectors and Conventional Blind Linear
Detectors…………………………………………………………………14 3.2 Subspacebased channel estimation…………………………………19 4. Enhanced Group Blind
Multiuser Detectors, Transformation Multiuser Detectors, and Enhanced Blind Channel
Estimation.........................................................22 4.1 Discussion of Group
Constraints……………………………………22 4.2 Enhanced Group Blind Multiuser
Detectors……26 4.3 Transformation of Group Blind Multiuser Detectors……………30 4.4
Simulation Resulat…………………………………………………………4 5.
Conclusions………………………………………………………54 5.1
Summary……………………………………………………………………54 5.2 Future
Work………………………………………………………………54 Appendix
A……………………………………………………………56 Appendix
B……………………………………………………………57
References……………………………………………………………58 List of Figures
Figure Page Fig. 1.1: FDMA TDMA and
CDMA……………………………………………2 Fig. 2.1: Downlink CDMA
System………………………………………………11 Fig. 2.2: Uplink CDMA
System……………………………………………………12 Fig. 2.3: Near-Far
Effect……………………………………………………………13 Fig. 4.1: RMSE of
channel estimation for asynchronous CDMA when the number multipath delays varies from
1 to 16..…………….....................................40 Fig.4.2 RMSE of channel estimation for
asynchronous CDMA when the input SNR varies from -5dB to
14dB…………………………………………………41 Fig.4.3 BER comparison of
different detectors for asynchronous CDMA when the input SNR varies from -5dB to 14dB
(7 asynchronous intracell
users)……………………………………………………………………42 Fig. 4.4 BER
comparison of different detectors for asynchronous CDMA when the input SNR varies from
-5dB to 14dB (8 asynchronous intracell users and 2 asynchronous
users)………………………………………………………43 Fig. 4.5 BER comparison of
different detectors for asynchronous CDMA when the input SNR varies from -5dB to 14dB
(8 asynchronous intracell users and 7 asynchronous
users).………………………………………………………44 Fig. 4.6 BER comparison of
different detectors for synchronous CDMA when the input SNR varies from -5dB to 14dB.
(8 synchronous intracell users and 2 asynchronous
users)………………………………………………………45 Fig. 4.7 BER comparison of
different detectors for synchronous CDMA when the input SNR varies from -5dB to 14dB.
(8 synchronous intracell users and 7 asynchronous
users)………………………………………………………46 Fig. 4.8 There are fixed 1
intercell users, and variable intracell users from 1 to 14. BER comparison is in uplink
SNR=3 dB…………………………………47 Fig. 4.9 There are fixed 1 intercell users, and
variable intracell users from 1 to 14. BER comparison is in downlink SNR=6
dB………………………………48 Fig. 4.10 BERs versus data block size. SNR=5 dB
Block size are from 100 to 5 000 in uplink. (8 asynchronous intracell users and 7
asynchronous users)………49 Fig. 4.11 BERs versus data block size. SNR=5dB Block size
are from 100 to 5000 in downlink. (8 synchronous intracell users and 7 asynchronous
users)……50 Fig. 4.12 BERs versus the rank of . SNR=3 dB the rank of are from 0 to 31 in
uplink (8 asynchronous intracell users and 2 asynchronous users)………51 Fig. 4.13 BERs
versus the rank of . SNR=6 dB the rank of are from 0 to 31 in downlink (8 synchronous
intracell users and 2 asynchronous users)……52
參
考
文
獻
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