本論文的研究目的直接序列分碼多工（DS/ CDMA）系統之功率控制設計和研究。在DS- CDMA系統中，不同的用戶從不同距離發射信號對於基地站有著不同的接收功率。這些不同的功率信號都會互相干擾。在功率控制其主要目的解決「近遠效率」問題。本論文的DS - CDMA功率控制系統考慮在接收器和發射器之間具有往返時延、通道衰落和雜訊。根據反饋的信干噪比（Signal-to-Interference-plus-Noise-Ratio，SINR）為控制器設計的依據與基礎，經由所設計的系統功率控制控制器，在訊號穩定的狀態之下，用戶端傳輸到基地台之功率達到最小之目的。在本論文另一部分所研究的通道傳輸中，使用不穩定具有變化之延遲時間，每一次系統會面臨到不同的延遲時間，由於延遲時間為不可預知的隨機變數，在控制器的設計上，將會增加控制器追尋穩定性的困難度。我們使用小腦模型控制器（Cerebella Model Articulation Controller ; CMAC）具有學習特性和收斂速度快的特性，對DS - CDMA系統架構學習。在本研究中CMAC的特點為快速收斂的區域推廣，並對時變延遲系統可以保證穩定。

This thesis proposes Cerebella Model Articulation Controller (CMAC) for power control of direct sequence code division multiple access (DS-CDMA) system. Since there is an infinite increase in number of users in a cellular radio system, limited resources must be efficiently used. Hence, closed-loop power control is important in resource planning. For DS-CDMA systems, there are different users transmitting signals to base stations, from various distances with difference power. In the DS-CDMA power control system architecture, round-trip delay, channel fading and noise. According to the SINR signal (Signal-to-Interference-plus-Noise-Ratio) feedback, design the controller to control the limited power between the base station and transmitter station and make the system to the stable. The other part of our research time-varying delay. In order to achieve the target power we use the CMAC.

Content

Abstract in Chinese............................................................................................I
Abstract in English...........................................................................................II
Contents...........................................................................................................III
List of Figures................................................................................................V
Chapter 1 Introduction  ...................................................................................1
1.1  Thesis Objective................................................................................1
1.2  Thesis Motivation..............................................................................2
1.3 Thesis Outline……………………………………………………….4
Chapter 2 Background…………………….. ....................................................5
2.1  Cerebellar Model Articulation Controller..........................................5
2.2  Direct-Sequence Code Division Multiple Access.............................6
Chapter 3　Cerebellar Model Articulation Controller.....................................9
	3.1  Methodology......................................................................................9
3.1.1 Mathematical preliminaries…………………………………..10
3.1.2 Learning method…………………………………………….. 11
3.1.3 Learning flow chart................………………………………13
3.1.4 Learning objectives …………………………………………..13
	3.1.4 .1Learning rate……..…………………………………….13
	3.1.4.2 The promotion of regional...…………………………...13
	3.1.4.3 Quantified……………….……………………………..15
3.2  Stability Analysis.............................................................................18
Chapter 4 CDMA Power Control as an Example……………………...…… 22
4.1 Background of CDMA Power Control…………………………..….22
4.1.1 Model of Channel…………………………………………….22
4.1.2 Model of Receiver……………………………………………24
4.1.3 Model of Transmitter…………………………………………25
4.2 CMAC for CDMA Power Control...………………………………..25
4.3 Comparisons of Combined and Separated Feedback/Feedforward
Time…………………………………………………………………28
4.4 Numerical Simulations……………………………………………...29
4.4.1 Effect of Channel Fading and Interference…………………...30
4.4.2 Effect on the Outage Probability……………………………..32
4.4.3 Effect of Number Mobile Users……………………………...35
4.5 Time-varying delay………………………………………………….36
4.5.1 Effect of Channel Fading and Interference …………………..39
4.5.2 Effect on the Outage Probability……………………………..41
4.5.3 Effect of Number Mobile Users……………………………...43
Chapter 5 Conclusions……………………………………………………… 45
Reference…………………………………………………………………….46








List of Figures

1.1 CDMA system block……………………………………………………...1
1.2 The CDMA system after improvement …………………………………. 2
3.1 Cerebella model articulation controller module ………………………...10
3.2 Cerebella model articulation controller mapping method ………………12
3.3 Cerebella model articulation controller mapped hypercube……………..12
3.4 Cerebella model articulation controller flow chart………………………14
3.5 GBF CMAC system……………………………………………………..15
3.6 S GBF CMAC system…………………………………………………...17
4.1 Closed-loop power control system………………………………………24
4.2 Simplified closed-loop power control system…………………………...26
4.3 The standard deviation σe vs. v (users = 10, data rate = 9.6 kbps, ς =0.9, d = Ts, σs = 4.3dB)……………………………………………………………. 31
4.4 The standard deviation σe vs. v (users = 10, data rate = 9.6 kbps, ς =0.9, d = Ts, σs = 4.3dB)…………………………………………………………….32
4.5 Po vs. v (users = 10, v = 80 km/h, ς = 0.9, d = Ts, σs = 4.3dB)………….33
4.6 Po vs. SINRmargin (users = 10, v = 80 km/h, ς = 0.9, d = Ts, σs = 4.3dB).34
4.7 σe vs. mobile users (ς = 0.9, d = Ts, σs = 4.3dB)………………………...35
4.8 Simplified closed-loop power control system with time-varying delay ...36
4.9 The standard deviation σe vs. v (users = 10, data rate = 9.6 kbps, ς =0.9, d = Ts, σs = 4.3dB)……………………………………………………………..39
4.10 The standard deviation σe vs. v (users = 10, data rate = 9.6 kbps, ς =0.9, d = Ts, σs = 4.3dB)……………………………………………………………..40
4.11 Po vs. v (users = 10, v = 80 km/h, ς = 0.9, d = Ts, σs = 4.3dB)…………42
4.12 Po vs. SINRmargin (users = 10, v = 80 km/h, ς = 0.9, d = Ts, σs = 4.3dB)………………………………………………………………………..43
4.13 σe vs. mobile users (ς = 0.9, d = Ts, σs = 4.3dB)……………………….44

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