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研究生:黃永發
研究生(外文):Yung-Fa Huang
論文名稱:應用於分碼多工通訊系統之平行干擾消除技術之研究
論文名稱(外文):Research on Parallel Interference Cancellation Techniques for DS-CDMA Communication Systems
指導教授:溫 志 宏
指導教授(外文):Jyh-Horng Wen
學位類別:博士
校院名稱:國立中正大學
系所名稱:電機工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:英文
論文頁數:114
中文關鍵詞:序列分碼多工多用戶檢測器平行干擾消除模糊推論機最小均方法
外文關鍵詞:DS-CDMAmultiuser detectorparallel interference cancellationfuzzy inference systemLMS algorithm
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本文主要是探討平行干擾消除(Parallel Interference Cancellation, PIC)多用戶檢測(Multiuser Detection)技術在序列分碼多工(Direct-Sequence Code-Division Multiple-Access, DS-CDMA)通訊系統上之效能改善。分碼多工通訊技術具備甚高之系統容量(System Capacity)潛力(Potentiality) ,是第三代行動通訊系統中最受青睞之架構之一,但在DS-CDMA系統中,用戶使用之非正交展頻碼在上連(uplink)傳輸時,均會有交互相關性(Cross-Correlation),因此用戶在接收訊號時就產生了多重進接干擾(Multiple Access Interference, MAI),當用戶數增加時,MAI成為系統效能惡化之主要因素。
近年來,在文獻中提出的次佳(Suboptimal)多用戶檢測器中,多級平行干擾消除法能有效地消除MAI;但當用戶數較多時,因大量MAI使效能惡化,且因其初始估計值是由傳統之Matched-Filter輸出端得到的,並不可靠,因此會有消除誤差(Cancellation Error)而造成嚴重之錯誤傳遞(Error Propagation)現象,以致無法有效提升系統容量。針對這種現象,部分平行干擾消除(Partial PIC, PPIC)應用部分消除權重(Partial Cancellation Weight, PCW)之作法確實可以有效地降低消除誤差,而比傳統之PIC有較佳之效能;因為適當之PCW與干擾信號之傳輸連路好壞(Link Quality)有關,於是,我們應用模糊推論機(Fuzzy Inference System, FIS)來根據所量測之通道資訊(Channel Information)推論出適當之消除權重(PCW),然後建置一個以FIS為基礎之部分平行干擾消除多用戶檢測器(Fuzzy-Based PPIC, FB-PPIC),期能將消除誤差降低至最低。由電腦模擬結果,我們發現以模糊推論機為基礎之多級部分平行干擾消除(FB-PPIC)多用戶檢測器,其效能比傳統之PIC及固定權重(Constant Weight)PPIC(CW-PPIC)都要好,也具有較高之強健性,在瑞雷衰退(Rayleigh Fading)通道之環境中,更為顯著。
但是,部分平行干擾消除之最佳消除權重還是無法真正反映出前級之位元估計之正確性,因此,本文進一步探討應用最小均方法(Least Mean Square, LMS)所調整之PCW特性,並進而分析其所調適(Adapt)之PCW之統計特性;並以所調整之PCW統計特性為基礎,應用最大後機率(Maximum A Posteriori Probability, MAP)檢測法則,來有效地判斷出前級之位元估計之正確性,於是我們提出了位元反向法(Bit Inversion, BI)來有效地將估計錯誤之位元改正過來。在作位元反向後,我們再加上一個完全的(Full)PIC,以期確實地將MAI全部消除。由電腦模擬結果,可知以我們提出之BI為基礎之三級完全PIC(BI-FPIC)檢測器在平瑞雷衰退(Flat Rayleigh Fading)通道之環境中,可達到單用戶之效能界限(Single-User-Bound),並且比其他之PPIC檢測器都要好。此外,電腦模擬結果顯示,BI-FPIC具有很高的抗遠近效應(Near-Far Resistance),在選頻衰退(Frequency Selective Fading)通道中也能有效地消除MAI。
為了更進一步改善BI-FPIC之效能,我們將一個部分消除權重表(Partial Weight Table, PWT)加到以BI為基礎之PPIC(BI-PPIC) 檢測器上,期能降低其消除誤差,而由電腦模擬結果知,BI-PPIC檢測器之效能只比BI-FPIC好一點,因此,我們可以說,我們提出之位元反向法(BI)可有效地將大部分之估計錯誤之位元改正過來,而後面之FPIC只產生很少之消除誤差,因此而得到非常好之系統效能。
The partial parallel interference cancellation (PPIC), which uses a partial cancellation weight (PCW) to reduce the cancellation error due to the incorrect interference estimates in the earlier stages, outperforms the conventional PIC (CPIC) in a direct-sequence code-division multiple-access (DS-CDMA) communication system when the system load is heavy. Thus, based on the adjustment of the cancellation weight according to the link quality of the interfering signal, we propose a fuzzy inference system (FIS) to establish a fuzzy-based PPIC (FB-PPIC) multiuser detector which then outperforms both CPIC and constant-weight PPIC (CW-PPIC) schemes.
However, the PCW in a PPIC is not able to guarantee the absolute correctness of the bit-decision in the previous stage. Therefore, in this thesis, we investigate the properties of the PCW adapted by the least-mean-square (LMS) adaptive filtering algorithm and then analyze the statistics of the adaptation PCW. Furthermore, with the maximum a posteriori probability (MAP) detection criterion based on the statistics of the adaptation-weights, the correctness of the bit-decisions can be effectively established. A bit-inversion (BI) procedure is then proposed to effectively invert the incorrect bit-decisions. After the BI procedure, a full PIC closely cancels the MAIs. Simulation results show that the proposed three-stage BI-based full PIC (BI-FPIC) detector can reach the single-user-bound and outperforms the PPIC schemes over a flat fading channel for CDMA systems. Moreover, the analytical and simulation results show that the proposed multistage BI-FPIC detector is highly near-far resistant and closely cancels the MAI over the frequency selective fading channels.
To improve the excess cancellation error of the proposed BI-FPIC detector, we establish a partial weight table to obtain appropriate partial weights for the BI-based PPIC scheme. Simulation results show that the proposed BI-PPIC only slightly outperforms the BI-FPIC scheme, even with a heaviest system load. Therefore, we conclude that the proposed BI procedure can invert most parts of the bit-decision errors of the higher received power users, then after the BI procedure, the full PIC incurs only a small cancellation error.
Abstract (Chinese) i
Abstract (English) iv
Acknowledgements vi
Contents vii
Abbreviations x
List of Tables xi
List of Figures xii
Publications xviii
Chapter 1 Introduction …………………………………………..……………………….… 1
1.1 Motivations …………………………………………………..………………….… 2
1.2 Organization of this Work ……………………………………..…….……………. 5
1.3 System Model of DS-CDMA Systems …………………………….……………… 6
1.3.1 Transmitter Model ………..………………………..………………………… 6
1.3.2 Channel Model …………………………………………..…………………… 8
1.3.3 Receiver Model ……………………………………….……………..………. 9
Chapter 2 Fuzzy-Based Parallel Interference Cancellation Multiuser Detection ……..…. 13
2.1 Conventional Parallel Interference Cancellation …………………..……………. 15
2.2 Partial Parallel Interference Cancellation ………………………..……….….…. 18
2.3 Fuzzy-Based Parallel Interference Cancellation …………………..………….…. 20
2.4 Simulation Results ………….………………..…………………………………. 27
2.4.1 Perfect Power Control …………….…………..………………………..……. 28
2.4.2 Near-Far Environments ………………………………..……………………. 30
2.4.3 Flat Fading Channels …………………………………..……..………..…… 32
2.4.4 Frequency Selective Fading Channels ……….…………..…………………. 36
2.4.5 Performance on the Imperfect Amplitude Estimation ……...………………. 39
2.5 Conclusions …………..…………………………………..………………..……. 41
Chapter 3 Partial Parallel Interference Cancellation with the Weights Adaptation Based
on LMS Algorithms ……………………………………………..………….…. 42
3.1 Adaptation of the PCW Based on LMS Algorithm …………..……..……….…. 43
3.2 Analysis on the Statistics of the Adaptation-Weight …………..……….…….…. 44
3.2.1 Analysis on Expectation of the Adaptation-Weight ………..……………..… 44
3.2.2 Analysis for Variance of the Adaptation-Weight …..…………..………….… 47
3.3 Performance Analysis for Bit-Inversion Procedure …………………..……….… 49
3.4 Simulation Results ………………………………………………….…...……… 51
3.4.1 Adaptation Properties of the Weight …………………..…………………… 51
3.4.2 Verification on the Theoretical and Simulation Results of the Statistics ..… 54
3.4.3 The Performance of MAP Criterion on the Adaptation-Weight …………… 58
3.4.4 Performance Evaluation of Bit-Inversion Based on LMS Algorithm ……… 61
3.5 Conclusions ………………………………………………………..……….……… 66
Chapter 4 Multistage Bit-Inversion Based Full Parallel Interference Cancellation …….… 68
4.1 Multistage Bit-Inversion Full Parallel Interference Cancellation …..…...……… 68
4.2 Performance Evaluation Based on Perfect Amplitude Estimation ….……..…… 72
4.2.1 Perfect Power Control ...…………………………..…………..……….…… 73
4.2.2 Near-Far Scenarios ….……………………………..…………………..…… 79
4.2.3 Flat Fading Channels ………………………………..…………….………. 83
4.2.4 Frequency Selective Fading Channels ……………………..…….……..…. 87
4.3 Evaluation of Performance Degradations due to Imperfect Amplitude
Estimation …………………………………………………………………….… 91
4.4 Conclusions ….……………………………………………………..………….... 97
Chapter 5 Bit-Inversion Based Partial Parallel Interference Cancellation Multiuser
Detection ……………………….…………………………………....……….... 98
5.1 Bit-Inversion Based PPIC ….………………………………………….……….... 98
5.2 Multistage Bit-Inversion PPIC Multiuser Detector ……………………....……. 101
5.3 Simulation Results …………………………………..…………..……….…….. 103
5.3.1 Near-Far Situations ………………………………….…………..……….……. 103
5.3.2 Flat Fading Channels …….………………….………………..…..….……. 105
5.3.3 Frequency Selective Fading Channels …….…………………....……....….. 106
5.4 Conclusion …….…………………………………...……………..………...…. 108
Chapter 6 Conclusions ..……………………………...…………………..………...…… 109
References ….………………………………………….....………………..…………...…. 111
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