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研究生:賴遠青
研究生(外文):Yuan-Quin Lei
論文名稱:適應性通道編碼調變模式變換最佳化之探討
論文名稱(外文):Adaptive Coded Modulation- Level Switching Optimization
指導教授:張文鐘
指導教授(外文):Wen Thong Chang
學位類別:碩士
校院名稱:國立交通大學
系所名稱:電信工程系
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:2003
畢業學年度:91
語文別:英文
論文頁數:58
中文關鍵詞:適應性通道編碼調變模式變換最佳化
外文關鍵詞:Adaptive Coded ModulationLevel Switching Optimization
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通訊系統的容量(capacity)是一個訊號強度與干擾強度的函數,因此,訊噪比(Signal to Noise Ratio)是影響通訊系統效能的最重要的問題,在有衰減變化的通道(fading channel)環境下,干擾的情形更是複雜,除了一般雜訊外,訊號強度的變化幅度更是影響通道容量的決定因素,因此,如何由訊噪比(SNR)擴及到載波干擾雜訊比(CINR, carrier to interference and noise ratio),來決定通道容量是一個重要的課題。為了能在不同的訊噪比的環境下尋找一個可以接受的通訊效能,我們使用了可變化的調變和錯誤改正碼(Adaptive modulation and adaptive forward error correcting code),以適應各種不同的通道環境。在無線通訊的系統中,通道是時時在變化的,我們用可變化的調變與編碼以應付這些不同的通道變化,而不同的調變與編碼技術會有不同的效能,我們的目標在尋找一最佳的決策方式,使的整體的效能最好,也就是調變後的系統,能夠達到最大的瞬間通道容量。而決策的考量,有最大的輸出(Maximize throughput)及最小化的錯誤率(Minimize Bit Error Rate & Block Error Rate)。

The capacity of the communication system is a function of signal to interference plus noise ratio. Thus the signal to noise ratio is most factor to influence the performance of communication systems. In fading channel, the communication problems become more complicated. We need adaptive transmission skill to replace traditional fix mode transmission. When the instantaneous SNR is high, more bit per symbol throughput mode is selected to increase the data rate. On the other hand, when the instantaneous SNR is low, less BPS throughput or robust mode is selected to decrease the bit error rate due to poor channel condition. In this thesis, we discuss the algorithms to find the optimum thresholds. These thresholds decide which mode is selected under certain instantaneous signal to noise ratio. When the modes have been determined, these optimum algorithms can find the optimum threshold to maximize the bit per symbol throughput and maintain target bit error rate.

Chapter 1 Introduction………………………………………………………………1
1.0 Motivation of adaptive transceiver…………………1
1.1 Adaptive Principle……………………………………………1
1.2 Channel Quality Estimation…………………………………1
1.3 Parameter Adaptation…………………………………………2
1.4 Outline of This Thesis………………………………………2
Chapter 2 Adaptive Modulation…………………………………4
2.1 Square-Constellation QAM…………………………4
2.1.1 Coherent Demodulation of Squared-Constellation QAM4
2.1.2 Performance of QAM in AWGN channel………………….4
2.1.3 Performance of QAM in Rayleigh Flat Fading Channel5
2.1.4 Performance of QAM in Nakagami Fading Channel………7
2.2 Type-I Star-Constellation QAM……………………7
2.2.1 Coherent Demodulation of SQAM in AWGN………8
2.2.2 Performance of SQAM in Rayleigh Flat Fading Channel…15
2.3 Adaptive Modulation for Narrow-Band Fading Channel...15
2.4 Adaptive Modulation in Nakagami Fading Channel…15
2.5 Some Practical Consideration of Wideband Adaptive Modulation…………………………………………16
2.5.1 Impact of Error Propagation……………………….16
2.5.2 Impact of Channel Estimation Latency……………18
Chapter 3 Adaptive Forward Error Correction Code…………21
3.1 Convolutional Encoder……………………………………….21
3.2 State and Trellis diagram for Convolutional Encoder………..23
3.3 Viterbi Algorithm…………………………………………….24
3.4 The soft decision of Viterbi Algorithm in Convolution Decoding……………………………………………………..27
3.5 Rate Compactable Punctured Convolutional Code…………..31
Chapter 4 Adaptive Transmission Mode Level Switching Optimization …32
4.0 General Model……………………………………………….32
4.1 Limiting the Peak Instantaneous Bit Error Rate……………..33
4.2 Torrance I method……………………………………………35
4.3 Simplified Torrance I method……………………………….36
4.4 Torrance II method- Cost function is a function of average SNR………………………………………..……………….38
4.5 Simplified Torrance II method…………………………….38
4.6 Lagrangian Method………………………………………..40
4.7 Lagrangian Method View to Torrance Method……………46
Chapter 5 Simulation and Conclusion……………………………………..47
5.1 System description…………………………………………47
5.1.1 System Overview……………………………………….47
5.1.2 FEC encoder…………………………………………….47
5.1.3 Modulation Mapping……………………………………48
5.1.4 Coded Modulation………………………………………50
5.1.5 Adaptive Algorithms…………………………………….51
5.2 Simulation Results…………………………………………...52
5.3 Conclusion…………………………………………………..57
5.4 Further Research and Suggestion……………………………57
Appendix A Reference…………………………………………………………58

[1] B. J. Choi and L. Hanzo, “Optimum mode switching levels for adaptive modulation systems”, IEEE GLOBECOM 2001
[2] J. Torrance and L. Hanzo, “Optimization of switching levels for adaptive modulation in a slow Rayleigh fading channel”, Electronics Letters, vol. 32, pp 1167-1169, 20 June 1996
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[10] R. Steele and W. Webb, “Variable rate QAM for data transmission over Rayleigh fading channels” in Proceedings of Wireless ’91, pp 1-14, IEEE 1991
[11] D. Goeckel, “Adaptive coding for fading channels using outdated fading estimates”, IEEE Transactions on Communications, vol 47, pp. 844-855, June 1999
[12] J. G. Proakis, Digital Communications. Mc-Graw Hill International Editions, 3rd ed, 1995
[13]D. Yoon, K. Cho, and J. Lee, “Bit error probability of M-ary Quadrature Amplitude Moduatin” in Proc. IEEE VTC 2000-Fall, vol. 5. pp 2422-2428, IEEE September 2000
[14]J. Hagenauer, “Rate Compatible puncture convolutional codes (RCPC) and their applications”, IEEE Transactions on Communications, vol 36, pp 389-4000, April 1998
[15]Stephen B. Wicker “Error Control Systems for digital communication and storage”, Prentice Hall
[16] L. Hanzo. T. H. Liew, B. L. Yeap, “Turbo coding, turbo equalization and space time coding for transmission over fading channels”, Wiley, 2002

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