臺灣博碩士論文加值系統

在本篇論文中，針對未來即將使用的5G毫米波通訊系統(5G millimeter-wave communications)，此系統應用於極高頻率的頻段，並且擁有大量的頻譜，其必然要使用的射頻(ratio frequency ,RF)功率放大器(power amplifier , PA)，將會對訊號偵測時產生巨大的挑戰。與傳統所使用的方案相比，傳統是在發送端(transmitter-ends)做非線性(nonlinear)的處理，而本篇論文提出在接收端(receiver-ends)做非線性等化(nonlinear equalization)，並且結合渦輪碼(turbo code)，提升估測訊號的可靠度，用來估測被多路徑通道(multipath channel)和非線性失真所干擾的訊號。由於非線性和邊緣積分(marginal integration)，其所涉及的後驗密度(posterior density)將難以分析，造成現存的線性等化都無法使用，故使用以蒙特卡羅序列重要性取樣(Monte-Carlo sequential importance sampling)為基礎的粒子濾波器(particle filter, PF)，利用概率質量(probability-mass)來近似。並且使用泰勒展開(Taylor’s series expansion)做區域線性化(local-linearization)，讓估測器趨近於現實的應用。如此一來，未知的傳送訊號將會被遞迴的偵測出來。模擬的結果也驗證了所提出的方法。不使用發射端高複雜度的預失真(pre-distortion)，而在接收端改用渦輪非線性等化(turbo nonlinear equalization)，讓毫米波通訊有了新的方向。

In the thesis, for the 5G millimeter-wave communications, which operating in extremely high frequency and have enormous bandwidth. It must use RF power amplifier which cause nonlinear distortion may pose great challenges to signal detections. Compare to classical schemes, which calibrate nonlinear distortions in transmitters, the thesis suggest a nonlinear equalization algorithm and combine turbo code to enhance reliability, with which the multipath channel and unknown symbols contaminated by nonlinear distortions and multipath interferences are estimated in receiver-ends. Attributed to the nonlinearity and marginal integration, the related posterior density is analytically hard and most existing linear equalization schemes may become invalid. To solve this problem, the Monte-Carlo sequential importance sampling based particle filtering is used, and the non-analytical distribution is approximated numerically by the evolving probability-mass. By applying the Taylor’s expansion, a local-linearization observation model is further constructed to facilitate the practical design of a sequential detector. Thus, the unknown symbols are detected recursively as new observations arrive. Simulation results validate the proposed joint detection scheme. By excluding transmitting pre-distortion of high complexity, the presented algorithm is specially designed for the receiver-end, which provides a promising framework to millimeter-wave communications.

第一章 緒論 1
1.1 前言 1
1.2 動機 1
1.3 論文架構 3
第二章 研究背景 4
2.1 多輸入多輸出 (MIMO) 4
2.2 空間多樣（Spatial Diversity）與空間多工（Spatial Multiplexing） 5
2.3 渦輪碼(Turbo Codes) 6
2.3.1 卷積碼(Convolutional Code) 7
2.3.2 交織器(Interleaver) 8
第三章 毫米波系統描述 10
3.1 非線性功率放大器(Nonlinear Power Amplifier) 10
3.2 毫米波通訊系統通道模擬(Channel Modeling for mm-Wave Communications) 12
3.3 訊號模型(Signal Model) 13
第四章 貝氏推論和粒子濾波 17
4.1 貝氏推論(Bayesian Inference) 17
4.2 順序重要性抽樣(Sequential Importance Sampling) 19
4.3 應用注意事項 21
第五章 非線性等化和訊號偵測 23
5.1 觀測點的區域線性化(Local Linearization of Observations) 23
5.2 序列非線性等化(Sequential Nonlinear Equalization) 24
5.3 接收端之實現(Implementations of Receiver) 28
5.4 延伸到多輸入多輸出系統(Extend to MIMO) 30
第六章 模擬結果 33
第七章 結論 49
參考文獻 50

[1]S. K. Yong, P. Xia, and A. Valdes-Garcia, 60 GHz Technology for Gbps WLAN and WPAN. Chichester, U.K.: Wiley, 2011.
[2]K. L. Shree, L. Penubaku, G. Nandihal,“ A novel approach of using security enabled Zigbee in vehicular communication,” 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)., 2016.
[3]Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for High Rate Wireless Personal Area Networks (WPANs): Amendment 2: Millimeter-Wave Based Alternative Physical Layer Extension, IEEE Std. 802.15.3c, 2009.
[4]IEEE Standard for Information technology-Telecommunications and information exchange between systems-Local and metropolitan area networks-Specific requirements-Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 3: Enhancements for Very High Throughput in the 60 GHz Band, IEEE Std 802.11ad-2012, 2012.
[5]M. C. Parker, G. Koczian, T. Quinlan, S. D. Walker.,“High capacity communications at 24 GHz and 60 GHz for converged 5G networking” 2015 20th European Conference on Networks and Optical Communications - (NOC)., pp. 1-6, 2015.
[6]K. Ohata et al., “1.25 Gbps wireless gigabit ethernet link at 60 GHz band,”in Proc IEEE MTT-S Int. Microw. Symp. Dig., Philadelphia, PA, USA, 2003, vol. 1, pp. 373–376.
[7]S. Kato et al., “Single carrier transmission for multi-gigabit 60-GHz WPAN system,” IEEE J. Sel. Areas Commun., vol. 27, no. 8, pp. 1466–1478, Oct. 2009.
[8]X. Zhang, L. R. Lu, R. Funada, C. S. Sum, and H. Harada, “Physical layer design and performance analysis on multi-Gbps millimeter-wave WLAN system,” in Proc IEEE ICCS, Singapore, Nov. 2010, pp. 92–96.
[9]C. R. Anderson and T. S. Rappaport, “In-building wideband partition loss measurements at 2.5 and 60 GHz,” IEEE Trans.Wireless Commun., vol. 3, no. 3, pp. 922–928, May 2004.
[10]M. Lei, C. S. Choi, R. Funada, H. Harada, and S. Kato, “Throughput comparison of multi-Gbps WPAN (IEEE 802.15.3c) PHY layer designs under non-linear 60-GHz power amplifier,” in Proc IEEE Int. Symp. PIMRC, Athens, Greece, Sep. 2007, pp. 1–5.
[11]E. Perahia et al., IEEE P802.11Wireless LANs TGad Evaluation Methodology, 2010.
[12]W. Gerhard and R. Knoechel, “Improvement of power amplifier efficiency by reactive Chireix combining, power back-off and differential phase adjustment,”in Proc IEEE MTT-IMS, San Francisco, CA, USA, Jun. 2006, pp. 1887–1890.
[13]N. Safari, J. P. Tanem, and T. Roste, “A block-based predistortion for high power-amplifier linearization,” IEEE Trans. Microw. Theory Techn., vol. 54, no. 6, pp. 2813–2820, Jun. 2006.
[14]A. Zhu et al., “Open-loop digital predistorter for RF power amplifiers using dynamic deviation reduction-based volterra series,” IEEE Trans.Microw. Theory Techn., vol. 56, no. 7, pp. 1524–1534, Jul. 2008.
[15]M. Rawat, K. Rawat, and F. M. Ghannouchi, “Adaptive digital predistortion of wireless power amplifiers/transmitters using dynamic real-valued focused time-delay line neural networks,” IEEE Trans. Microw. Theory Techn., vol. 58, no. 1, pp. 95–104, Jan. 2010.
[16]G. Montoro, P. L. Gilabert, E. Bertran, A. Cesari, and J. A. Garcła, “An LMS-based adaptive predistorter for cancelling nonlinear memory effects in RF power amplifiers,” in Proc. APMC, Bangkok, Thailand, Dec. 2007, pp. 1–4.
[17]L. Ding et al., “A robust digital baseband predistorter constructed using memory polynomials,” IEEE Trans. Commun., vol. 52, no. 1, pp. 159–165, Jan. 2004.
[18]A. Doucet, N. de Freitas, and N. Gordon, Eds., Sequential Monte Carlo Methods in Practice. New York, NY, USA: Springer-Verlag, 2001.
[19]A. Doucet, “On sequential simulation-based methods for bayesian filtering,”Stat. Comput., vol. 10, no. 3, pp. 197–208, Jul. 2000.
[20]P. M. Djuric et al., “Particle filtering,” IEEE Signal Process. Mag., vol. 20,no. 5, pp. 19–38, Sep. 2003.
[21]J. Miguez and P. M. Djuric, “Blind equalization of frequency-selective channels by sequential importance sampling,” IEEE Trans. Signal Process., vol. 52, no. 10, pp. 2738–2748, Oct. 2004.
[22]D. Crisan, “Particle filters: A theoretical perspective,” in SequentialMonte Carlo Methods in Practice, A. Doucet, J. F. G. de Freitas, and N. J. Gordon, Eds. New York, NY, USA: Springer-Verlag, 2001, pp. 17–38.
[23]J. Liu and R. Chen, “Blind deconvolution via sequential imputations,”J. Amer. Stat. Assoc., vol. 90, no. 430, pp. 567–576, Jun. 1995.
[24]Z. G. Yang and X. D. Wang, “A sequential Monte Carlo blind receiver for OFDM systems in frequency-selective fading channels,” IEEE Trans. Signal Process., vol. 50, no. 2, pp. 271–280, Feb. 2002.
[25]T. Bertozzi, D. Le Ruyet, G. Rigal, and H. Vu-Thien, “Joint data-channel estimation using the particle filtering on multipath fading,” in Proc. ICT, Papeete, Tahiti, 2003, pp. 1284–1289.
[26]Y. Huang and P. M. Djuric, “A new importance function for particle filtering and its application to blind detection in flat fading channels,” in Proc. IEEE ICASSP, 2002, pp. 1617–1620.
[27]J. H. Kotecha and P. M. Djuric, “Sequential Monte Carlo sampling detector for Rayleigh fast-fading channels,” in Proc. IEEE ICASSP, 2000, pp. 61–64.
[28]Kyeongyeon Kim, Kalantarova, N., Kozat, S.S., Singer, A.C., “Linear MMSE-Optimal Turbo Equalization Using Context Trees”, IEEE Transactions On Signal Processing, Vol. 61, No. 12, pp. 3041-3055, Jun. 15, 2013
[29]J. C. Pedro, N. B. Carvalho, and P. M. Lavrador, “Modeling nonlinear behavior of band-pass memoryless and dynamic systems,” in Proc. IEEE MTTS Int. Microw. ymp. Dig. MTT-IMS, Philadelphia, PA, USA,Jun. 2003, pp. 2133–2136.
[30]S. K. Yong, “TG3c channel modeling sub-committee final report,” IEEE 802.15 TG3c Working Group for Wireless Personal Area Network (WPAN), IEEE 802.15-07-0584-01-003c, May 2007.
[31]K. Sato, H. Sawada, Y. Shoji, and S. Kato, “Channel model for millimeter-wave WPAN,” in Proc. IEEE 18th Int. Symp. PIMRC, Athens, Greece, Sep. 2007, pp. 1–5.
[32]B. Li, Z. Zhou, W. X. Zou, X. B. Sun, and G. L. Du, “On the efficient beam pattern training for 60 GHz wireless personal area networks,” IEEE Trans. Wireless Commun., vol. 12, no. 2, pp. 504–515, Feb. 2013.
[33]Z. Y. Xiao, X. G. Xia, D. P. Jin, and N. Ge, “Iterative eigenvalue ecomposition and multipath-grouping Tx/Rx joint beam-formings for millimeter-wave communications,” IEEE Trans. Wireless Commun., vol. 14, no. 3, pp. 1595–1607, Mar. 2015.
[34]P. Shanmugam, H. G. Yeh, J. Lee, D. Chang,“ Transmitter beam-forming techniques for indoor millimeter wave communication,” 2017 Annual IEEE International Systems Conference (SysCon)., 2017.
[35]Z. Zhao, W. Na, V. M. Reddy, G. Reddy, Q. Zhang,“ Multi-band behavioral modeling of power amplifier using carrier frequency-dependent time delay neural network model,” 2017 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization for RF, Microwave, and Terahertz Applications (NEMO).,2017.
[36]D. Gapillout, C. Maziere, E. Ngoya, S. Mons,“ A reliable methodology for experimental extraction of power amplifier dynamic volterra model,”in 2015 Integrated Nonlinear Microwave and Millimetre-wave Circuits Workshop (INMMiC).2015.
[37]A. Zhu,“ Behavioral modeling for digital predistortion of RF power amplifiers: from Volterra series to CPWL functions,” 2016 IEEE Topical Conference on Power Amplifiers for Wireless and Radio Applications (PAWR),2016.
[38]S. J. Julier and K. U. Jeffery, “A new extension of the Kalman filter to nonlinear systems,” in Proc. SPIE 11th Int. Symp. Aerosp. Defense Sens., Simul. Controls, Multi Sensor Fusion, Tracking Resource Manage. II, 1997, p. 182.