注冊(cè) | 登錄讀書好,好讀書,讀好書!
讀書網(wǎng)-DuShu.com
當(dāng)前位置: 首頁(yè)出版圖書科學(xué)技術(shù)工業(yè)技術(shù)無線電電子學(xué)、電信技術(shù)窄帶干擾和沖激噪聲的抑制與消除關(guān)鍵技術(shù)研究(英文版)

窄帶干擾和沖激噪聲的抑制與消除關(guān)鍵技術(shù)研究(英文版)

窄帶干擾和沖激噪聲的抑制與消除關(guān)鍵技術(shù)研究(英文版)

定 價(jià):¥119.00

作 者: 劉思聰 著
出版社: 清華大學(xué)出版社
叢編項(xiàng): 清華大學(xué)優(yōu)秀博士學(xué)位論文叢書
標(biāo) 簽: 暫缺

ISBN: 9787302585152 出版時(shí)間: 2021-07-01 包裝: 平裝
開本: 16開 頁(yè)數(shù): 228 字?jǐn)?shù):  

內(nèi)容簡(jiǎn)介

  現(xiàn)代通信系統(tǒng)對(duì)傳輸?shù)目煽啃?、有效性和穩(wěn)定性的需求與日俱增。然而,廣泛存在的復(fù)雜化、隨機(jī)化、高強(qiáng)度的窄帶干擾與沖激噪聲是限制系統(tǒng)性能的重大瓶頸,傳統(tǒng)方法難以有效消除其影響?!墩瓗Ц蓴_和沖激噪聲的抑制與消除關(guān)鍵技術(shù)研究(英文版)》針對(duì)這一技術(shù)難點(diǎn),基于經(jīng)典數(shù)字通信系統(tǒng)理論和新型稀疏恢復(fù)理論,從新型物理層幀結(jié)構(gòu)設(shè)計(jì)、z優(yōu)時(shí)頻聯(lián)合交織、基于壓縮感知的稀疏恢復(fù)等方面介紹窄帶干擾與沖激噪聲抑制與消除關(guān)鍵技術(shù),適用于無線通信、電力線通信、智慧照明網(wǎng)絡(luò)等多種系統(tǒng)。

作者簡(jiǎn)介

  劉思聰,現(xiàn)任廈門大學(xué)信息科學(xué)與技術(shù)學(xué)院通信工程系助理教授。曾任華為技術(shù)有限公司網(wǎng)絡(luò)技術(shù)研究部高級(jí)研究工程師。分別于2012年、2017年獲得清華大學(xué)電子工程系電子信息科學(xué)與技術(shù)專業(yè)學(xué)士學(xué)位、信息與通信工程專業(yè)博士學(xué)位,評(píng)為清華大學(xué)優(yōu)秀博士畢業(yè)生、清華大學(xué)優(yōu)秀博士學(xué)位論文、北京市優(yōu)秀畢業(yè)生。主要研究領(lǐng)域?yàn)閷拵Ф嗝襟w傳輸、通信系統(tǒng)噪聲干擾抑制、稀疏信號(hào)處理、壓縮感知、稀疏學(xué)習(xí)等。已發(fā)表36篇SCI/EI收錄論文,獲國(guó)家發(fā)明專利授權(quán)7項(xiàng),為寬帶電力線通信物理層國(guó)家標(biāo)準(zhǔn)起草人,擔(dān)任多個(gè)IEEE權(quán)威期刊審稿人,兼任多項(xiàng)國(guó)際學(xué)術(shù)雜志客座編委和國(guó)際會(huì)議TPC成員。

圖書目錄

Contents








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 Description 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 Description 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 Description 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 Description 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

本目錄推薦

掃描二維碼
Copyright ? 讀書網(wǎng) ranfinancial.com 2005-2020, All Rights Reserved.
鄂ICP備15019699號(hào) 鄂公網(wǎng)安備 42010302001612號(hào)