Full-Duplex Wireless Communications Systems (eBook)

Preface 6
Contents 8
Acronyms 11
1 Introduction 13
1.1 Full-Duplex Wireless Systems 13
1.2 SI-Cancellation Techniques 15
1.2.1 Antenna SI-Cancellation Techniques 16
1.2.2 RF SI-Cancellation Techniques 16
1.2.3 Baseband SI-Cancellation Techniques 17
1.3 Applications of Full-Duplex Communications 18
1.4 Book Organization 20
References 22
2 Self-Interference-Cancellation in Full-Duplex Systems 24
2.1 SI Channel Modelling 24
2.2 Analog RF Cancellation Stage 25
2.3 Digital SI-Cancellation 26
2.4 Channel Estimation in Full-Duplex Systems 27
2.5 Effect of Transmitter Impairments in SI-Cancellation 29
2.6 Cancellation of Nonlinear Distortions 30
2.7 Spatial Cancellation 32
2.8 Chapter Summary 34
References 34
3 Limiting Factors in Self-Interference Cancellation 37
3.1 System Model and SI-Cancellation Architectures 38
3.1.1 Complex-Baseband Signal Representation 41
3.1.2 Residual SI Due to Phase Noise 44
3.1.3 Quantization and Clipping Noise from ADC 44
3.1.4 Transceiver Impairments and Noise 46
3.1.5 Auxiliary Component-Induced Impairments 47
3.1.6 Baseband SI-Cancellation 48
3.2 Performance Evaluation: Illustrative Results 49
3.2.1 System Specifications 49
3.2.1.1 SI Channel Modelling 49
3.2.1.2 Transceiver Parameters 50
3.2.2 Residual Self-Interference After RF Cancellation Stage 50
3.2.2.1 Quantization Noise 52
3.2.2.2 Limiting Behaviour of the RF Cancellation Stage 54
3.2.3 Residual SI After the Baseband SI-Cancellation Stage 55
3.3 Conclusion 58
Appendix 58
References 59
4 Self-Interference Channel Estimation and Cancellation Using Compressed-Sensing and Subspace Approaches 61
4.1 Full-Duplex System Model 62
4.2 Compressed-Sensing-Based RF Cancellation Stage 66
4.3 Subspace-Based Baseband Cancellation Stage 70
4.3.1 Subspace-Based Technique 72
4.3.2 Resolving the Ambiguity Matrix C 75
4.4 Illustrative Results 79
4.5 Chapter Summary 85
Appendix: Proof of (4.60) 86
References 88
5 Widely-Linear Subspace-Based Self-Interference-Cancellation 90
5.1 Widely-Linear Channel Estimator 91
5.1.1 Real-Modulated Symbols 92
5.1.2 Complex-Modulated Symbols 94
5.1.3 Subspace-Based Algorithm 95
5.2 Resolving the Ambiguity Term 98
5.3 Simulation Results 103
5.4 Chapter Summary 111
References 111
6 Maximum Likelihood Self-Interference Cancellation 113
6.1 System Model 114
6.2 ML Estimator 116
6.2.1 Closed-Form Solution 117
6.2.2 Iterative ML Estimator 119
6.3 Phase Noise Suppression 121
6.4 Simulation Results 125
6.4.1 Performance in the Absence of Phase Noise 125
6.4.2 Performance in the Presence of Phase Noise 130
6.4.3 Simulink Platform 131
6.5 Chapter Summary 132
Appendix 1: Proof of limT ?? R0K0I0d"0365 RR0K0I0d"0365 RR0K0I0d"0365 RR0K0I0d"0365 R = R 133
Appendix 2: Covariance Matrix R0K0I0d"0365 RR0K0I0d"0365 RR0K0I0d"0365 RR0K0I0d"0365 Rpn 137
Appendix 3: Proof of Convergence 139
Appendix 4: Stochastic CRB 140
References 141
7 Active Signal Injection for Self-Interference-Cancellation 142
7.1 Novel Active Signal Injection for SI-Cancellation 144
7.2 Tone Reservation for SI-Cancellation 145
7.3 Constellation Relaxation for SI-Cancellation 150
7.4 Combination of Both Methods 155
7.5 Simulation Results 155
7.6 Chapter Summary 162
Appendix 1: Development of the Cost Function for the Tone Reservation Method 163
Appendix 2: On the Invertibility of the Matrix M 165
References 166
8 Conclusions and Future Work 167
8.1 Concluding Remarks 167
8.2 Future Work 169