臺灣博碩士論文加值系統

3G的通訊時代即將來臨，其中最為吸引人之處為提供多種傳輸速率的服務，隨著多種傳輸速率可供選擇，如何配合傳輸功率，選擇最適當傳輸速率變成眾人最有興趣的問題之一。如果能夠針對這個問題，得到出色的解決方法，則可以預見在傳輸量，系統容量，都有顯著的提升。
這篇論文就是要設計整合傳輸功率控制和傳輸速率的演算法，針對設計的演算法，尋求適當的參數，以期得到最佳的傳輸表現，並且解決功率控制中target Eb/No設定的問題，使整套演算法更為完整，得以在真實系統中呈現其傑出的表現。
論文的第一部份，我們假設已知通道特性，針對通道特性選取最適當的target Eb/No給傳輸功率控制機制。再參考3GPP的粗略指導方針提出了Constrained Power Based Rate Adaptation algorithm，其特色在於同時考慮傳輸功率控制，傳輸速率控制，並且可以非常有效的使用傳輸功率。
第二部份則是在不知通道特性的情況下，為滿足需要的FER，而設計了Turbo code iteration based dynamic target Eb/No setting algorithm。以較少量的傳輸功率，便能得到相同的FER，此特性令人印象深刻。
第三部份則是把第二部份的演算法做了些改變，使得Constrained Power Based Rate Adaptation algorithm即使在未知通道特性的情況下，亦能只需花費少量的時間即找出適當的target Eb/No。如此一來，Constrained Power Based Rate Adaptation algorithm將可以在實際系統中展現其突出性能。

Abstract
Third generation systems are designed for multirate communication, it’s the most charming part of third generation. How to combine power control and choosing the suitable data rate is one of the most popular issues. If we can find an excellent solution for this problem, we believe we will have an obvious promoting in throughputs and system capacity.
Design power control and rate control algorithm jointly is the main point of this work. Searching the suitable parameters that need for our algorithm to improve the performance. And we discuss how to set the target Eb/No in power control mechanism to complete the whole algorithm. Then we can apply this algorithm in real system and see its impressive performance in real worlds.
At the beginning of this paper, we assume the suitable target Eb/No for certain channel is known. And we refer the guidelines in 3GPP to design “Constrained Power Based Rate Adaptation algorithm”. This algorithm considers power and rate control jointly, and using transmission power very efficiently.
In the second part of this paper, we proposed “FER estimation based dynamic target Eb/No setting algorithm” to satisfy required FER when the channel is unknown. The impressive point of this algorithm is using less power to satisfy required FER.
At the last part, we modify “FER estimation based dynamic target Eb/No setting algorithm” then we can use a short time to find suitable target Eb/No for “Constrained Power Based Rate Adaptation algorithm” even the characteristic of the channel is unknown. Therefore, “Constrained Power Based Rate Adaptation algorithm” can show it’s excellent performance in real system.

Chapter 1: Preface 1
1.1簡介 1
1.2 Problem Formulation 2
1.2.1 傳輸功率控制 2
1.2.2 傳輸速率控制 2
1.2.3 結合傳輸速率控制和傳輸功率控制 3
1.3 章節內容 3
Chapter 2： Background 4
2.1 傳輸功率控制 4
2.1.1傳輸功率控制的基本機制 4
2.1.2 Channel Coding (Turbo Codes) [2] 6
2.1.3 SIR measurement 17
2.1.4 Target Eb/No 19
2.2 Rate Control 21
Chapter 3：Rate and Power adaptation for WCDMA 24
3.1 Introduction 24
3.2 The key parameters in this algorithm 25
3.3 The rate adaptation algorithm based on Constrained-power rate adaptation algorithm 27
3.3.1 Description of the Constrained-power based rate adaptation algorithm 27
3.3.2 Criterion for choosing spreading factor 30
3.3.3 Criterion for setting Pmax & Pmin 31
3.4 Simulation Platform 31
3.5 Simulation Results 32
3.5.1 Comparison of different Target Eb/No 32
3.5.2 Comparison of different rate adaptation algorithm 33
3.5.3 Impact of different Nup & Nlow on throughput and transmission power 35
3.5.4 Impact of Pmax and Pmin 37
3.6 Conclusion 39
Chapter 4: SIR measurement 40
4.1 Introduction 40
4.2 Soft output Viterbi algorithm (SOVA)-based SIR estimation 40
4.2.1 Turbo encoder/decoder 40
4.2.2 Channel quality metric 41
4.3 Numerical results 45
A: Simulation Model 45
B: Discussion 46
4.4 Conclusion 50
Chapter 5: Dynamic Target Eb/No setting in CLPC for the WCDMA System 51
5.1 Motivation 51
5.2 Background 52
5.2.1 Previous Work 52
5.2.2 Amazing FER estimation algorithm 52
5.3 The dynamic Target Eb/No setting algorithm based on estimated FER 54
5.3.1 Turbo code iteration based dynamic target Eb/No setting algorithm 54
5.3.2 Criterion for choosing the amount of increasing/decreasing Target Eb/No 55
5.3.3 Criterion for choosing the weight to count Avg_iterationest 56
5.4 Simulation Platform 57
5.5 Simulation Results 58
5.5.1 Comparison of different Dynamic Target Eb/No setting algorithm 58
5.5.2 Compare the performance for different Dynamic Target Eb/No algorithm when the channel is changing 60
5.6 Conclusion 61
Chapter 6: Apply the Dynamic Target Eb/No setting to the Constrained-power based rate adaptation algorithm 62
6.1 Motivation 62
6.2 The Principle to choose fixed Target Eb/No for Constrained-Power rate adaptation algorithm 63
6.3 Simulation platform 65
6.4 Numerical Results 65
6.4.1 Doppler frequency = 10 Hz 65
6.4.2 Doppler frequency = 50 Hz 67
6.5 Conclusion 69
Chapter 7: Conclusion & Future work 70
7.1: Conclusion 70
7.2: Future work 71
Reference: 72
附件:模擬程式 74
Turbo encoder program 74
Turbo decoder program 74
Interleaver program 83
De-interleaver program 86
Walsh code program 87
Scramble code program 87
Constrained tx-power rate adaptation algorithm program 88
SNR measurement based rate adaptation algorithm program 94
Reference case for rate adaptation program 98
Rayleigh fading program 101
CRC based dynamic target Eb/No setting program 103
Turbo code iteration based dynamic target Eb/No setting algorithm program 105

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