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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 李學智(Hsueh-Jyh Li) | |
| dc.contributor.author | Yao-Chia Chan | en |
| dc.contributor.author | 詹曜嘉 | zh_TW |
| dc.date.accessioned | 2021-06-15T06:44:34Z | - |
| dc.date.available | 2016-08-22 | |
| dc.date.copyright | 2011-08-22 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-08-20 | |
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Viswanath, Fundamentals of wireless communication. Cambridge University Press, 2005. [22] E. Biglieri, R. Calderbank, A. Constantinides, A. Goldsmith, A. Paulraj, H. V. Poor, MIMO Wireless Communications. Cambridge University Press, 2010. [23] L.H. Ozarow, S. Shamai, A. D. Wyner, “Information theoretic considerations for cellular mobile radio,” IEEE Transactions on Vehicular Technology, vol.43, no.2, pp.359-378, May 1994. [24] Xiqi Gao; Bin Jiang; Xiao Li; A. B. Gershman, M. R. McKay, “Statistical Eigenmode Transmission Over Jointly Correlated MIMO Channels,” IEEE Transactions on Information Theory, vol.55, no.8, pp.3735-3750, Aug. 2009. [25] P. Eggers. “Angular Propagation Descriptions Relevant for Base Station Adaptive Antenna Operations,” Wireless Personal Communication, vol.11, pp. 3-29, October 1999. [26] A. T. James, “Distributions of Matrix Variates and Latent Roots Derived from Normal Samples,” The Annals of Mathematical Statistics, Vol. 35, No. 2, pp. 475-501, June, 1964. [27] M. Kang, M. S. Alouini, “Capacity of correlated MIMO Rayleigh channels,” IEEE Transactions on Wireless Communications, vol.5, no.1, pp. 143- 155, Jan. 2006. [28] P. Billingsley, Probability and Measure. John Wiley & Sons, 1995. [29] W. Rudin, Principles of Mathematical Analysis. McGraw-Hill, 1976. [30] “Section 26: Characteristic function,” class notes for ICM 5404, Graduate Institute of Communication Engineering, National Chiao-Tung Univeristy, Fall 2009. [31] RUSK Channel Sounder, available at http://www.channelsounder.de. [32] D. M. Pozar, Microwave Engineering. John Wiley, 2005. [33] R. W. Chang, “Synthesis of band-limited orthogonal signals for multi-channel datatransmission,” Bell Labs Technical Journal, vol. 45, pp. 1775-1796, Dec. 1966. [34] A. V. Oppenheim, Discrete-Time Signal Processing. Prentice Hall, 2008. [35] T. M. Schmidl, D. C. Cox, “Robust frequency and timing synchronization for OFDM,” IEEE Transactions on Communications, vol.45, no.12, pp.1613-1621, Dec 1997. [36] R. Negi, J. Cioffi, “Pilot tone selection for channel estimation in a mobile OFDM system,” in International Conference on Consumer Electronics, 1998, pp. 466- 467. [37] T.-D. Chiueh, P.-Y. Tsai, OFDM Baseband Receiver Design for Wireless Communications. John Wiley and Sons, 2007. [38] Agilent Technologies Technical Staff, User’s guide of Agilent Technologies ESG Vector Signal Generator, Agilent Technologies, 2003. [39] Tektrnoix Technical Staff, Printable Online Help of RSA 6100A Series Real-time Spectrum Analyzers, Tektronix Inc., 2010. [40] D. Chizhik, J. Ling, P.W. Wolniansky, R. A. Valenzuela, N. Costa, K. Huber, “Multiple-input-multiple-output measurements and modeling in Manhattan,” IEEE Journal on Selected Areas in Communications, vol.21, no.3, pp. 321-331, April 2003. [41] T. J. Willink, “Characteristics of urban vehicular MIMO channels at different frequencies,” in European Conference on Antennas and Propagation, 2009, pp.645-649. [42] N. R. Goodman, “Statistical Analysis Based on a Certain Multivariate Complex Gaussian Distribution (An Introduction),” The Annals of Mathematical Statistics, Vol. 34, No. 1, pp. 152-177, March 1963. [43] Y.-C. Lu (private communication), 2011. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/48020 | - |
| dc.description.abstract | 在通訊系統中要能有效率地提升資料傳送速度，除了擴張頻寬之外，在理論上也可以透過增加傳送、接收兩端的天線數目，形成所謂的多輸入多輸出（Multiple-Input Multiple-Output, MIMO）系統，來提升通道容量。然而在MIMO系統中，對於通道的統計性質假設與現實環境不合，例如未考慮天線所看到的通道彼此之間的相關性，則會高估此種系統理論上的潛力。
在本論文中將回顧文獻中數種應用於分析MIMO系統所使用的解析通道模型，其中Weichselberger等人所提出之模型有許多解析通道模型之一般化的形式，故將特別著重此模型討論。除了介紹Weichselberger模型的數學型式外，本論文亦提出模型的物理詮釋，將實際的電波傳播現象與模型參數連接起來。為了檢視模型在戶外到室內環境的適用性，以及前述之物理詮釋是否合理，在本論文中以以通用信號量測儀器組合出以正交多工分頻信號為基礎的MIMO通道探測儀，所得到實地量測結果，並以通道容量做為衡量標準，驗證模型的適用性與物理詮釋的合理性。除了驗證模型之外，也可以透過模型的參數，了解不同環境、系統組態、以及天線陣列種類對於MIMO通道特性的影響。 | zh_TW |
| dc.description.abstract | Prediction in theory shows that data rate can be efficiently further raised by adding multiple antennas to both of the transmitter and receiver in addition to expanding transmission bandwidth, forming so called Multiple-Input Multiple-Output (MIMO) system. However, improper channel modeling, such as lacking in consideration of correlation in channels between antennas, may leads to over-optimistic results.
In this thesis several analytic MIMO channel models are reviewed. Emphasis is laid on the model proposed by Weichselberger et al. since it encompasses various analytic models. In addition to the math formulation, the physical interpretation is proposed to link the model parameters to physical wave propagation phenomenon. With MIMO channel capacity as evaluation metric, and the MIMO OFDM-based channel sounder developed with general-purposed equipments, the validity of both physical interpretation and the statistical behavior of the model are examined in an outdoor-to-indoor environment. In addition, with the model parameters estimated with measurement results, one may have a view on the characteristics of MIMO channel seen by the system with some specific configurations. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T06:44:34Z (GMT). No. of bitstreams: 1 ntu-100-R98942029-1.pdf: 3330779 bytes, checksum: e720929da6ea0b36c41d77efbcec699e (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
致謝 iii 論文摘要 v Thesis Abstract vii Table of Contents ix List of Figures xiii Chapter 1 Introduction 1 Chapter 2 Weichselberger MIMO Channel Model 5 2.1 Modeling Methodology 6 2.2 Analytic Models and Their Deficiencies 8 2.2.1 I.I.D. model 8 2.2.2 Kronecker model 9 2.2.3 Virtual Channel Representation 11 2.3 Weichselberger Model 15 2.3.1 Notations and Model Assumptions 15 2.3.2 Model Formulation 17 2.3.3 Comparison with SVD 18 2.3.4 Special Cases 20 2.4 Physical Interpretation 21 2.4.1 Eigen-structure of Correlation Matrix 22 2.4.1.1 Receiver-Side Eigen-structure: Single Incoming Wave 22 2.4.1.2 Receiver-Side Eigen-structure: Multiple Incoming Waves 25 2.4.1.3 Transmitter-Side Eigen-structure 31 2.4.2 Model Assumptions 33 2.4.3 Coupling Matrix 35 2.5 Summary 39 Chapter 3 A Statistical View on Capacity of MIMO Channel 41 3.1 Capacity of Wireless MIMO Channel 43 3.1.1 The Capacity of Single-link Wireless Channel 43 3.1.1.1 Ergodic Capacity 44 3.1.1.2 Outage Probability 45 3.1.1.3 Outage Capacity 46 3.1.2 MIMO Extension 46 3.1.2.1 I.I.D. Model 48 3.1.2.2 Weichselberger Model 49 3.1.2.3 Kronecker Model 54 3.2 Statistics of Capacity of One-sided Correlated MIMO Channel 54 3.3 Fourier Series Technique 57 3.4 Distribution of Capacity of One-sided Correlated Channel 62 3.5 Summary 65 Appendix 3.1 Sphere-Packing Argument on (3.1) and (3.8) 65 Appendix 3.2 Proof of Theorem 3.1 74 Chapter 4 OFDM-based MIMO Channel Sounder 79 4.1 Motivation 80 4.2 OFDM Basics 83 4.2.1 Signal Model 84 4.2.2 Coarse Timing Synchronization 87 4.2.3 Channel Estimation 91 4.2.3.1 Least-Sqaure Method 91 4.2.3.2 DFT-Interpolation Method 92 4.2.4 Fine Timing Synchronization 93 4.2.5 Channel Sounding with OFDM signal 95 4.3 System Architecture 97 4.3.1 The Core Equipments 97 4.3.2 The Architecture 99 4.4 Program Control Flow 101 4.4.1 Assignment Stage 103 4.4.2 Alignment Stage 103 4.4.3 Acquisition Stage 104 4.5 Features and Limitations 105 Appendix 4.1 Derivation of equation (4.5) 107 Chapter 5 Outdoor-to-Indoor MIMO Channel Measurement and Analysis 109 5.1 Experiment Settings 110 5.1.1 Environment Descriptions 111 5.1.2 Instrument Setup and the Measurement Data 111 5.2 Parameter Extraction 114 5.3 Eigen-patterns and Coupling Matrices at 700MHz 116 5.4 Comparisons of Different Antenna Spacing 126 5.5 Comparisons of Different Frequency Bands 130 5.6 Summary 132 Appendix 5.1 Electromagnetic Simulation Settings with of Figure 5.6 132 Chapter 6 Conclusions 137 Reference 139 | |
| dc.language.iso | en | |
| dc.title | 相關性多輸入多輸出通道之解構與分析 | zh_TW |
| dc.title | Deconstructing Correlated Multiple-Input Multiple-Output Channel and Its Analysis | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 林丁丙(Ding-Bing Lin),闕志達(Tzi-Dar Chiueh),莊俊雄(Gene C.H. Chuang) | |
| dc.subject.keyword | 相關性多輸入多輸出（MIMO）通道,Weichselberger模型,特徵場型,耦合矩陣,通道容量,MIMO通道探測儀,MIMO通道量測, | zh_TW |
| dc.subject.keyword | Correleted Multiple-Input Multiple-Out (MIMO) Channel,Weichselberger model,eigen-pattern,coupling matrix,channel capacity,MIMO Channel sounder,MIMO channel measurement, | en |
| dc.relation.page | 143 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2011-08-20 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
| 顯示於系所單位： | 電信工程學研究所 | |
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