記
錄 6771
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狀
NC094FJU00428007
態
助
教
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
沈煥鈞
生
(中
)
研
究
Huan-Chun Shen
生
(英
)
論
文 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
名
稱
(中
)
論
文
名 A Novel Group Blind Multiuser Detection for DS-CDMA Systems with Multipaths
稱
(英
)
其
他
題
名
指
導
教 余金郎
授
(中
)
指
導
教 Jung-Lang Yu
授
(英
)
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位 碩士
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94
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文 英文
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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
字
(中
)
關
鍵
Group DS-CDMA Group Blind Multiuser Detection
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(英
)
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
摘
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
要
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
(中
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。
The 3rd generation mobile communication will base on code-division multiple-access
(CDMA) system, because CDMA systems can provide more capacity than timedivision 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
摘
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
要
users, the corresponding signature matrix can be estimated and the group-blind
(英
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
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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
Subspace-based 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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