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书名 | 窄带干扰和冲激噪声的抑制与消除关键技术研究(英文版)(精)/清华大学优秀博士学位论文丛书 |
分类 | 科学技术-工业科技-电子通讯 |
作者 | 刘思聪 |
出版社 | 清华大学出版社 |
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简介 | 内容推荐 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最新研究成果,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、如何精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。 目录 1 Introduction 1.1 Research Background and Aims 1.1.1 An Overview of Digital Communication Systems 1.1.2 Noises and Interferences 1.1.3 Characteristics and Detrimental Effects of NBI and IN 1.2 Related Works and Challenges 1.2.1 Related Works and Problems on NBI Mitigation 1.2.2 Related Works and Problems on IN Mitigation 1.3 Key Research Problems and Research Aims 1.4 Main Works and Contributions 1.5 Structural Arrangements References 2 System Model and Fundamental Knowledge 2.1 An Overview of Broadband Digital Communication Systems 2.1.1 OFDM-Based Block Transmission 2.1.2 Key Techniques of OFDM-Based Block Transmission 2.2 Frame Structure of Broadband Digital Communication Systems 2.2.1 Structure of Preamble in Frame Header 2.2.2 Structure of Data Sub-Frame 2.3 Narrowband Interference Model and Impulsive Noise Model 2.3.1 Narrowband Interference Model 2.3.2 Impulsive Noise Model 2.4 Fundamentals of Sparse Recovery Theory 2.4.1 Compressed Sensing and Sparse Recovery 2.4.2 Structured Compressed Sensing Theory 2.4.3 Sparse Bayesian Learning Theory. References 3 Synchronization Frame Design for NBI Mitigation 3.1 Introduction 3.1.1 Problem Description and Related Research 3.1.2 Research Aims and Problems 3.2 Signal Model 3.3 Synchronization Frame Structure Design for NBI Mitigation 3.4 Timing and Fractional CFO Synchronization 3.5 Integer CFO Estimation and Signaling Detection with NBI 3.6 Performance Analysis of the Algorithms 3.7 Simulation Results and Discussions 3.8 Conclusion References 4 Optimal Time Frequency Interleaving with NBI and TIN 4.1 Introduction 4.1.1 Problem Description and Related Research 4.1.2 Research Aims and Problems 4.2 System Model 4.3 Design of Optimal Time-Frequency Joint Interleaving Method 4.3.1 Interleaving with Maximizing Time Diversity 4.3.2 Interleaving with Maximum Frequency Diversity 4.4 Performance Analysis of the Algorithms 4.5 Simulation Results and Discussions 4.6 Conclusion References 5 Sparse Recovery Based NBI Cancelation 5.1 Introduction 5.1.1 Problem Description and Related Research 5.1.2 Research Aims and Problems 5.2 System Model 5.3 Compressed Sensing Based NBI Reconstruction 5.3.1 System Model of Frame Structure 5.3.2 Temporal Differential Measuring 5.3.3 Compressed Sensing Based Reconstruction Algorithm 5.3.4 Simulation Results and Discussions 5.4 Structured Compressed Sensing Based NBI Recovery 5.4.1 NBI and Signal Models in MIMO Systems 5.4.2 Spatial Multi-dimensional Differential Measuring 5.4.3 Structured SAMP Algorithm 5.4.4 Simulation Results and Discussions 5.5 Sparse Bayesian Learning Based NBI Recovery 5.5.1 System Model 5.5.2 BSBL Based NBI Reconstruction for CP-OFDM 5.5.3 Simulation Results and Discussions 5.6 Performance Analysis of Algorithms 5.7 Conclusion References 6 Sparse Recovery Based IN Cancelation 6.1 Introduction 6.1.1 Problem Description and Related Research 6.1.2 Research Aims and Problems 6.2 System Model 6.3 Prior Aided Compressed Sensing Based IN Cancelation 6.3.1 OFDM System Model with Impulsive Noise 6.3.2 Priori Aided Compressed Sensing Based IN Recovery 6.3.3 Simulation Results and Discussions 6.4 Structured Compressed Sensing Based IN Cancelation 6.4.1 MIMO System Model with Impulsive Noise 6.4.2 Spatially Multi-dimensional IN Measurement 6.4.3 Structured Prior Aided SAMP (SPA-SAMP) Algorithm 6.4.4 Simulation Results and Discussions 6.5 Compressed Sensing Joint Cancelation of NBI and IN 6.5.1 Time-Frequency Combined Measuring 6.5.2 Time-Frequency Combined Recovery of NBI and IN 6.5.3 Simulation Results and Discussions |
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