窄带干扰和冲激噪声的抑制与消除关键技术研究(英文版) 清华大学出版社 下载 mobi 免费 pdf 百度网盘 epub 2025 在线 电子书

窄带干扰和冲激噪声的抑制与消除关键技术研究(英文版) 清华大学出版社精美图片
》窄带干扰和冲激噪声的抑制与消除关键技术研究(英文版) 清华大学出版社电子书籍版权问题 请点击这里查看《

窄带干扰和冲激噪声的抑制与消除关键技术研究(英文版) 清华大学出版社书籍详细信息

  • ISBN:9787302585152
  • 作者:暂无作者
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  • 出版时间:2021-08
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  • 价格:101.20
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  • 开本:32开
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  • 更新时间:2025-01-19 00:50:04

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内容简介:

本书总结了近年来窄带干扰和冲激噪声的抑制与消除关键技术的近期新研究成果,从如何抑制窄带干扰对同步的影响、如何提升通信系统在窄带干扰与冲激噪声下的时频交织性能、如何准确重构并消除冲激噪声与窄带干扰等科学问题切入,围绕“加扰”以抑制、“分集”以规避、“重构”以消除噪声干扰的研究思路,提出了有效、新型的框架与算法,从多个角度入手,全面提升了下一代宽带通信系统抑制与消除窄带干扰和冲激噪声的能力。本书可供通信信号处理、无线通信等领域的本科生和研究生,以及从事相关理论研究、算法设计与工程实践的读者参考。


书籍目录:

1 Introduction 1

1.1 Research Background and Aims 1

1.1.1 An Overview of Digital Communication Systems 3

1.1.2 Noises and Interferences 7

1.1.3 Characteristics and Detrimental Effects of NBI and IN 10

1.2 Related Works and Challenges 13

1.2.1 Related Works and Problems on NBI Mitigation 13

1.2.2 Related Works and Problems on IN Mitigation 15

1.3 Key Research Problems and Research Aims 18

1.4 Main Works and Contributions 19

1.5 Structural Arrangements 21

References 24

2 System Model and Fundamental Knowledge 31

2.1 An Overview of Broadband Digital Communication Systems 31

2.1.1 OFDM-Based Block Transmission 31

2.1.2 Key Techniques of OFDM-Based Block Transmission 34

2.2 Frame Structure of Broadband Digital Communication Systems 38

2.2.1 Structure of Preamble in Frame Header 39

2.2.2 Structure of Data Sub-Frame 41

2.3 Narrowband Interference Model and Impulsive Noise Model 42

2.3.1 Narrowband Interference Model 42

2.3.2 Impulsive Noise Model 46

2.4 Fundamentals of Sparse Recovery Theory 49

2.4.1 Compressed Sensing and Sparse Recovery 50

2.4.2 Structured Compressed Sensing Theory 52

2.4.3 Sparse Bayesian Learning Theory 55

References 57

3 Synchronization Frame Design for NBI Mitigation 61

3.1 Introduction 61

3.1.1 Problem Deion and Related Research 61

3.1.2 Research Aims and Problems 63

3.2 Signal Model 63

3.3 Synchronization Frame Structure Design for NBI Mitigation 65

3.4 Timing and Fractional CFO Synchronization 66

3.5 Integer CFO Estimation and Signaling Detection with NBI 69

3.6 Performance Analysis of the Algorithms 71

3.7 Simulation Results and Discussions 74

3.8 Conclusion 77

References 77

4 Optimal Time Frequency Interleaving with NBI and TIN 79

4.1 Introduction 80

4.1.1 Problem Deion and Related Research 80

4.1.2 Research Aims and Problems 81

4.2 System Model 82

4.3 Design of Optimal Time-Frequency Joint Interleaving Method 83

4.3.1 Interleaving with Maximizing Time Diversity 84

4.3.2 Interleaving with Maximum Frequency Diversity 85

4.4 Performance Analysis of the Algorithms 88

4.5 Simulation Results and Discussions 90

4.6 Conclusion 94

References 96

5 Sparse Recovery Based NBI Cancelation 99

5.1 Introduction 99

5.1.1 Problem Deion and Related Research 99

5.1.2 Research Aims and Problems 102

5.2 System Model 103

5.3 Compressed Sensing Based NBI Reconstruction 105

5.3.1 System Model of Frame Structure 105

5.3.2 Temporal Differential Measuring 109

5.3.3 Compressed Sensing Based Reconstruction Algorithm 112

5.3.4 Simulation Results and Discussions 117

5.4 Structured Compressed Sensing Based NBI Recovery 123

5.4.1 NBI and Signal Models in MIMO Systems 124

5.4.2 Spatial Multi-dimensional Differential Measuring 125

5.4.3 Structured SAMP Algorithm 128

5.4.4 Simulation Results and Discussions 132

5.5 Sparse Bayesian Learning Based NBI Recovery 136

5.5.1 System Model 136

5.5.2 BSBL Based NBI Reconstruction for CP-OFDM 141

5.5.3 Simulation Results and Discussions 147

5.6 Performance Analysis of Algorithms 151

5.7 Conclusion 156

References 157

6 Sparse Recovery Based IN Cancelation 161

6.1 Introduction 161

6.1.1 Problem Deion and Related Research 161

6.1.2 Research Aims and Problems 162

6.2 System Model 163

6.3 Prior Aided Compressed Sensing Based IN Cancelation 165

6.3.1 OFDM System Model with Impulsive Noise 165

6.3.2 Priori Aided Compressed Sensing Based IN Recovery 166

6.3.3 Simulation Results and Discussions 168

6.4 Structured Compressed Sensing Based IN Cancelation 169

6.4.1 MIMO System Model with Impulsive Noise 169

6.4.2 Spatially Multi-dimensional IN Measurement 172

6.4.3 Structured Prior Aided SAMP (SPA-SAMP) Algorithm 174

6.4.4 Simulation Results and Discussions 176

6.5 Compressed Sensing Joint Cancelation of NBI and IN 179

6.5.1 Time-Frequency Combined Measuring 179

6.5.2 Time-Frequency Combined Recovery of NBI and IN 182

6.5.3 Simulation Results and Discussions 186

6.6 Algorithm Performance Evaluation 190

6.7 Conclusion 198

References 199

7 Conclusions 201

7.1 Contributions 201

7.1.1 Anti-NBI Frame Design and Synchronization Method 202

7.1.2 Optimal Time-Frequency Combined Interleaving 203

7.1.3 Sparse Recovery Based NBI and IN Cancelation 204

7.2 Further Research 206

References 208


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