Intro
Supervisor's Foreword
Preface
Acknowledgements
Contents
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