陳光禎臺灣大學：電信工程學研究所魏逢時Wei, Fong-ShihFong-ShihWei2007-11-272018-07-052007-11-272018-07-052006http://ntur.lib.ntu.edu.tw//handle/246246/58892Abstract Spatial antenna diversity has been important in improving the performance of the wireless communication systems and supporting high data rate services. Many of the space-time coding schemes applied to multi-antenna systems assume that perfect synchronization to achieve the expected performance gain. However, the inaccuracy of frequency offset estimation caused by the mismatch of the oscillators between the transmitter and receiver and/or Doppler shift would degrade the performance. In this thesis we investigate the problem of frequency offset estimation in multiple-transmit-antenna systems to find out whether space diversity can provide diversity gain to frequency offset estimation or not. The performance of the maximum likelihood (ML) estimator and the Cramer-Rao lower bound (CRLB) are shown and also the asymptotic CRLB. The optimal training sequences designed based on obtaining the optimum performance are discussed.Contents 摘要 ….……………………………………………………...…………I 誌謝 ........................................................................................................III Abstract…………………………………………………….....................V List of Figures..........................................................................................XI List of Tables..........................................................................................XV Chapter 1 Introduction………………………………………...............….1 Chapter 2 Overview of Transmit Space Diversity……………………......5 2.1 Wireless Multi-Input and Single-Output Channel Model………………..…...5 2.1.1 Multi-Path Fading Propagation………………………….........................5 2.1.2 The Statistical Model for the Fading Channel……………………….......6 2.1.3 Wireless MISO Channel Model…………………………........................7 2.2 Transmitter Space Diversity………………………………………...…….......8 2.2.1 Two Kinds of Transmitter Space Diversity…………………………..….8 2.2.2 Signal Models and Assumptions………………………………………...9 Chapter 3 Transmit Space Diversity in Frequency Estimation………….13 3.1 Maximum Likelihood Estimation……………………………………..…….13 3.2 Performance Analysis of ML Estimation…………………………………….16 3.2.1 Expectation and Variance………………………………………………16 3.2.2 Crammer Rao Lower Bound (CRLB)………………………………….17 3.2.3 Asymptotic (Large-sample) CRLB…………………………………….20 3.3 Design of the Optimum Training Sequence………………………...……….22 3.3.1 Optimization Criterion…………………………………………………22 3.3.2 Average Asymptotic CRLB…………………………………………….24 3.4 Diversity Gain for Frequency Estimation……………………..…………….25 3.4.1 Space-Time Block Orthogonal Training Sequence…………………….26 3.4.1.1 Performance of Space-Time Block Orthogonal Training Sequence………………………………………………………….27 3.4.1.2 Statistical Analysis of the Performance of Space-Time Block Orthogonal Training Sequence…………………………………...28 3.4.2 Hadamard Sequence……………………………………………………29 3.4.2.1 Performance of Hadamard Sequence…………………………….30 3.4.2.2 Statistical Analysis of the Performance of Hadamard Sequence……………………………………………………………….32 Appendix 3 Mean and Variance of the ML Estimator………………………..…..35 Chapter 4 Simulations and Discussions………………………………...37 4.1 Performance of ML Estimation in Rayleigh Flat-Fading Channels……….37 4.1.1 Random Sequence: MISO vs. SISO……………………………………38 4.1.2 Space-time Block Orthogonal Training Sequence: MISO vs. SISO…...41 4.1.3 Hadamard Sequence: MISO vs. SISO………………………………….44 4.2 The Effect of Timing Offset………………………………………………....52 4.3 Performance of ML Estimation in Frequency-Selective Channels...……...…55 Chapter 5 Conclusions and Future Work………………………………. 59 Bibliography………………………………………………………...…. 63656275 bytesapplication/pdfen-US頻率偏移估測分集frequency offset estimationdiversitythesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/58892/1/ntu-95-R93942100-1.pdf