臺灣博碩士論文加值系統

隨著手機普及化，人們對於手機在各方面的需求與日漸增，其中最為顯著的便是極高的資料傳輸速率，為此第五代行動通也預計即將在2020年正式上路。現今的學術界及產業界皆投身於第五代行動通訊系統的發展，期許能夠滿足未來極高的資料傳輸量之要求。為了因應第五代通訊系統，我們實驗室提出了一個可能的技術，並稱之為巨量天線徑分多重接取(MDMA)蜂巢式行動通訊系統。在此系統運作模式下，本論文中針對先前實驗室已探討出的上行傳輸技術進行整合，借此先了解技術整合後的效能，而這些技術中包含了典型卡曼濾波器、大數決策輔助路徑篩選、 平行干擾消除、交織碼調變、ZC循環位移領航序列，再結合巨量天線的特性使位元錯誤率下降以及減少通道估計誤差。在觀察整合系統之效能後，接著再進一步分析出原始傳輸模型的一些弱點。為了針對此項弱點進行優化，本論文提出新的傳輸模型，並將上述的整合傳輸技術加入到優化過的傳輸模型中進行模擬。整合後與優化後的系統效能皆呈現於我們的模擬結果中，我們也針對此兩種傳輸模型對於系統效能的影響進行討論與分析。

The requirement for all aspects of mobile phones increases along with the popularization of mobile phones. Among all of them, the most obvious part is very high data rate. Therefore, the fifth generation (5G) mobile communication systems are scheduled to start formally in 2020. Both the academia and industry devote themselves to the development of the 5G communication systems at present and look forward to satisfy the requirement of very high data rate. In response to the research of 5G communication systems, we propose a possible solution which is named massive antenna multipath division multiple access (MDMA) cellular system. In this thesis, we first integrate all the transmission techniques which have been researched previously for this system. And these techniques include Kalman filter (KF)、majority vote aided path selection、parallel interference cancellation (PIC)、trellis-coded modulation (TCM) and cyclic-shifted ZC sequences. After integrating them with massive antenna, the BER and channel estimation error are reduced. Furthermore, we find there are some weak points in the original transmission model. So we also propose a refined system with a new transmission model which also works well with all the transmission techniques above. Simulation results of both the integrated and the refined MDMA systems are given and discussed in details.

中文摘要 I
Abstract II
誌 謝 III
Contents IV
List of Tables VI
List of Figures VII
Chapter 1. Introduction 1
1.1 Introduction 1
1.2 The 5G Massive Antenna MDMA Cellular System 2
1.3 Thesis Organization 3
Chapter 2. System Models and Channel Model 5
2.1 Integrated System and Refined System 5
2.2 The Proposed 5G Channel Model 8
2.3 MUD with Parallel Interference Cancellation 10
2.3.1 MUD at initial stage 11
2.3.2 MUD at PIC stage 17
Chapter 3. Techniques for Channel Estimation 24
3.1 Cyclic-shifted ZC Pilot Sequences 24
3.1.1 Conventional ZC Pilot Sequences 24
3.1.2 Cyclic-shifted ZC Pilot Sequences 26
3.2 Majority Vote Aided Path Selection 28
3.2.1 Conventional Path Selection Method 28
3.2.2 Majority Vote Aided Path Selection Method 29
3.3 Kalman Filter(KF) Based Channel Estimation 32
3.3.1 Channel Feature Assumptions 32
3.3.2 Introduction to the Kalman Filter(KF) 34
3.3.3 KF Based CE in the MDMA System 35
Chapter 4. Trellis-Coded Modulation 39
4.1 Concept of Trellis-Coded Modulation 39
4.2 Performance Analysis 41
4.2.1 Four-State Trellis Code for 8-PSK Modulation 41
4.2.2 Eight-State Trellis Code for QPSK Modulation 44
Chapter 5. Simulation Results 49
5.1 Simulation Parameters 49
5.2 Simulation Results and Discussions 51
5.2.1 Performances under single cell transmission scenario, ideal synchronization and ideal power control 51
5.2.2 Performances model under multi-cell transmission scenario, ideal synchronization and ideal power control 54
5.2.3 Performances under multi-cell transmission scenario without ideal synchronization and ideal power control 55
Chapter 6. Conclusion 60
Reference 62
Appendix 64

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