Gregorio / González / Schmidt Signal Processing Techniques for Power Efficient Wireless Communication Systems

Practical Approaches for RF Impairments Reduction
1. Auflage 2019
ISBN: 978-3-030-32437-7
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 269 Seiten

Reihe: Signals and Communication Technology

This book presents a synthesis of the research carried out in the Laboratory of Signal Processing and Communications (LaPSyC), CONICET, Universidad Nacional del Sur, Argentina, since 2003. It presents models and techniques widely used by the signal processing community, focusing on low-complexity methodologies that are scalable to different applications. It also highlights measures of the performance and impact of each compensation technique. The book is divided into three parts: 1) basic models 2) compensation techniques and 3) applications in advanced technologies. The first part addresses basic architectures of transceivers,  their component blocks and  modulation techniques. It also describes the performance to be taken into account, regardless of the distortions that need to be compensated. In the second part, several schemes of compensation and/or reduction of imperfections are explored, including linearization of power amplifiers, compensation of the characteristics of analog-to- digital converters and CFO compensation for OFDM modulation. The third and last part demonstrates the use of some of these techniques in modern wireless-communication systems, such as full-duplex transmission, massive MIMO schemes and Internet of Things applications.

Prof. Dr. Fernando Gregorio received the B.Sc. degree from the Universidad Tecnologica Nacional (UTN), Bahía Blanca, Argentina, the M.Sc. degree in electrical engineering from the Universidad Nacional del Sur (UNS), Bahía Blanca and the D.Sc. degree in electrical engineering from the Helsinki University of Technology (HUT), Espoo, Finland, in 2007. Since 2008, he has been with the Departamento de Ingenieria Eléctrica y Computadoras at UNS, Argentina. He is currently a Senior Researcher of the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) of Argentina. His research interests include power amplifier nonlinearities and RF imperfection in MIMO-OFDM systems, Massive MIMO and RF energy harvesting.Dr. Gustavo José González was born in Bahía Blanca, Argentina. He received the B.Sc. degree in 2007, and the Ph.D. degree in 2012 from Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina. In 2007, he joined the Instituto de Investigaciones en Ingeniería Eléctrica and the Departamento de Ingeniería Eléctrica y de Computadoras at UNS. He has been a Researcher with the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) since 2014. His research interests include synchronization and interference analysis for OFDM(A) systems with half- and full-duplex operation mode.Dr. Christian A. Schmidt received the B.Sc. degree in Electronic Engineering and the Ph.D. degree in Engineering from Universidad Nacional del Sur, Bahía Blanca, Argentina, in 2005 and 2012, respectively. Since 2015, he holds a position as researcher at Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). His research interests include nonlinear dynamic systems modeling and compensation, post-processing techniques for distortion reduction in Analog-to-digital converters, PAPR reduction, and signal processing for communications systems including OFDM, UWB, Full-duplex and massive MIMO.
Prof. Dr. Juan Cousseau received the B.Sc. from the Universidad Nacional del Sur (UNS), Bahia Blanca, Argentina, in 1983, the M.Sc. degree from COPPE/ Universidade Federal do Rio de Janeiro (UFRJ), Brazil, in 1989, and the Ph.D. from COPPE/UFRJ, in 1993, all in electrical engineering. Since 1984, he has been with the undergraduate Department of Electrical and Computer Engineering at UNS. He is a senior researcher of the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) of Argentina. He has been involved in scientific and industry projects with research groups from Argentina, Brazil, Spain, USA, Finland and South Africa. He is coordinator of the Signal Processing and Communication Laboratory (LaPSyC) at UNS. He is Senior member of the IEEE. He was IEEE Circuits and Systems Chair of the Argentine Chapter, from 1997 to 2000, and member of the Executive Committee of the IEEE Circuits and Systems Society during 2000/2001 (Vice-president for Region 9). He participates in the IEEE Signal Processing Society Distinguished Lecturer Program 2006. He is currently Director of 'Instituto de Investigaciones en Ingeniería Eléctrica - Alfredo Desages', CONICET - UNS. His research interests are related to adaptive and statistical signal processing with application to modern broadband wireless communications.

Autoren/Hrsg.

Gregorio, Fernando

González, Gustavo

Schmidt, Christian

Cousseau, Juan

Inhaltsverzeichnis

1;Preface;7
2;Contents;8
3;Acronyms;13
3.1;3;13
3.2;5;13
3.3;6;13
3.4;A;13
3.5;B;14
3.6;C;14
3.7;D;14
3.8;E;14
3.9;F;15
3.10;G;15
3.11;H;15
3.12;I;15
3.13;K;16
3.14;L;16
3.15;M;16
3.16;N;16
3.17;O;17
3.18;P;17
3.19;Q;17
3.20;R;17
3.21;S;18
3.22;T;18
3.23;U;18
3.24;W;18
3.25;Z;19
4;Part I Definitions and Models;20
4.1;1 Introduction;21
4.1.1;1.1 Motivation: 5G Wireless Systems and Its Requirements;21
4.1.2;1.2 Basic Components of the Communication System;23
4.1.3;1.3 Implementation Issues;25
4.1.4;1.4 Main Contributions of the Book;26
4.1.5;1.5 Outline of the Book;26
4.1.6;References;27
4.2;2 Digital Block and RF Front-End Models;28
4.2.1;2.1 Introduction;28
4.2.2;2.2 Metrics for Wireless Communication Systems;30
4.2.2.1;2.2.1 Link Budget;30
4.2.2.2;2.2.2 Nonlinearities;31
4.2.2.3;2.2.3 Noise Figure;33
4.2.2.4;2.2.4 Error Vector Magnitude;34
4.2.3;2.3 Wireless Channel Models;34
4.2.3.1;2.3.1 Coherence Bandwidth and Coherence Time;36
4.2.4;2.4 Baseband Block: Multicarrier Modulation;37
4.2.5;2.5 Power Amplifiers: Nonlinear Distortion;39
4.2.5.1;2.5.1 PAPR and Power Efficiency;40
4.2.5.2;2.5.2 Power Amplifier Models;42
4.2.5.2.1;2.5.2.1 Memoryless Power Amplifier Models;42
4.2.5.2.2;2.5.2.2 Power Amplifier Models with Memory;44
4.2.6;2.6 Low Noise Amplifiers;44
4.2.7;2.7 Mixers: Phase and Amplitude Imbalances;45
4.2.8;2.8 Local Oscillator: Phase Noise;47
4.2.8.1;2.8.1 Millimeter-Wave Phase Noise Modeling;49
4.2.9;2.9 Analog-to-Digital Converters (ADC);51
4.2.9.1;2.9.1 ADC: Performance Metrics;51
4.2.9.2;2.9.2 Metrics of Spectral Purity;52
4.2.9.3;2.9.3 Transfer Function Linearity Metrics;52
4.2.10;2.10 Digital-to-Analog Converters (DAC);54
4.2.10.1;2.10.1 Binary Weighed DAC;54
4.2.10.2;2.10.2 Segmented DAC;55
4.2.11;2.11 Summary of the Key Points;55
4.2.12;References;55
4.3;3 Energy Consumption;58
4.3.1;3.1 Introduction;58
4.3.2;3.2 Energy Efficiency and Spectral Efficiency;59
4.3.3;3.3 Digital Block and Front-End Power Consumption Models;62
4.3.3.1;3.3.1 Radio Frequency Front-End;62
4.3.3.2;3.3.2 Baseband Processing;68
4.3.4;3.4 ADC: Power Consumption, Resolution, and Sampling Frequency Trade-Off;71
4.3.4.1;3.4.1 ADC Figures of Merit and Approximate Power Consumption;72
4.3.4.2;3.4.2 Lower Bound on Power Consumption for Noise-Limited ADCs;73
4.3.5;3.5 Short-Range and Long-Range Links;74
4.3.6;3.6 Power Consumption Scaling;78
4.3.6.1;3.6.1 Bandwidth Dependence;79
4.3.6.2;3.6.2 Number of Antennas;80
4.3.6.3;3.6.3 Data Rate (Constellation Size);80
4.3.7;3.7 Energy Efficiency of Digital Compensation Techniques;81
4.3.8;3.8 Summary of the Key Points;83
4.3.9;References;83
5;Part II Digital Compensation Techniques;87
5.1;4 Power Amplifiers;88
5.1.1;4.1 Power Amplifiers and Multicarrier Signals;88
5.1.1.1;4.1.1 Operation Point: Power Consumption vs Distortion Trade-Off;89
5.1.2;4.2 Linearization Techniques;91
5.1.3;4.3 Figures of Merit: In-Band and Out-of-Band Distortion;93
5.1.4;4.4 Digital Predistortion Techniques;94
5.1.4.1;4.4.1 Baseband Predistortion Techniques: Implementation Issues;96
5.1.5;4.5 Receiver-Side Compensation Techniques;98
5.1.5.1;4.5.1 Decision-Aided Reconstruction of Clipped Signals;98
5.1.5.2;4.5.2 Power Amplifier Nonlinearity Cancellation (PANC);99
5.1.6;4.6 A Case of Study: Linearization of Class AB and Envelope Tracking PAs;104
5.1.6.1;4.6.1 Partitioned Predistorter;104
5.1.6.1.1;4.6.1.1 Partitioned DPD Parameter Estimation;105
5.1.6.2;4.6.2 Partitions Allocations;107
5.1.6.2.1;4.6.2.1 Input Distribution-Based Partition Allocation;108
5.1.6.2.2;4.6.2.2 ? Law Partitions Allocation;110
5.1.6.2.3;4.6.2.3 Iterative Partitions Allocation Technique;111
5.1.6.3;4.6.3 Numerical Evaluation;111
5.1.7;4.7 Summary of the Key Points;115
5.1.8;References;115
5.2;5 ADC in Broadband Communications;120
5.2.1;5.1 ADC Architectures;120
5.2.1.1;5.1.1 Flash: High Conversion Speed, Low Resolution;121
5.2.1.2;5.1.2 SAR: High Resolution, Low Conversion Speed;122
5.2.1.3;5.1.3 Sigma-Delta: Higher Resolution with Low Quantization, Oversampling, and Noise Shaping;122
5.2.1.4;5.1.4 Combined Structures;123
5.2.1.4.1;5.1.4.1 Pipelined ADCs: Increased Resolution;123
5.2.1.4.2;5.1.4.2 Time-Interleaved ADCs: Increased Sampling Speed;124
5.2.2;5.2 Traditional (Narrowband) Compensation Techniques;124
5.2.2.1;5.2.1 Integral Nonlinearity and Differential Nonlinearity Models;125
5.2.2.2;5.2.2 Look-Up Tables;126
5.2.2.3;5.2.3 Dithering;127
5.2.3;5.3 Novel Compensation Techniques Amenable for Wideband Sampling;128
5.2.3.1;5.3.1 Model Inversion: Nonlinear Dynamic Models;129
5.2.3.1.1;5.3.1.1 Behavioral Model of Continuous-Time ?? Modulators;129
5.2.3.1.2;5.3.1.2 Volterra Model and Post-compensation of a Continuous-Time Modulators;133
5.2.3.1.3;5.3.1.3 Performance in Post-compensation;135
5.2.3.2;5.3.2 Wideband Compensation of High-Performance ADCs;137
5.2.3.3;5.3.3 Mismatch Errors in TIADCs;141
5.2.3.3.1;5.3.3.1 Signal Representation;142
5.2.3.3.2;5.3.3.2 Off-Line Estimation;143
5.2.3.3.3;5.3.3.3 On-Line Estimation;144
5.2.3.3.4;5.3.3.4 Compensation;145
5.2.4;5.4 Additional Considerations: Training Signals for Measurement-Based Post-compensation;147
5.2.5;5.5 Summary of Key Points;151
5.2.6;References;151
5.3;6 Frequency Offset and Phase Noise;155
5.3.1;6.1 Effects of the CFO and Phase Noise in the System Performance;155
5.3.1.1;6.1.1 Critical Applications: High Frequency Oscillators and High-Speed Vehicles;156
5.3.1.2;6.1.2 Effects of Carrier Frequency Offset and Phase Noise in OFDM;158
5.3.2;6.2 Estimation Techniques for the Downlink (Single User Case);160
5.3.3;6.3 Estimation and Compensation Techniques for the Uplink (Multiuser Case);165
5.3.3.1;6.3.1 CFO Compensation for OFDMA;167
5.3.3.2;6.3.2 CFO Compensation for Multiuser FBMC;170
5.3.4;6.4 Summary of the Key Points;176
5.3.5;References;177
6;Part III RF Imperfection in Novel Technologies;180
6.1;7 Full-Duplex Communication Systems;181
6.1.1;7.1 System Model;181
6.1.1.1;7.1.1 Full-Duplex Transceivers;182
6.1.1.2;7.1.2 Full-Duplex Relays;183
6.1.2;7.2 Self-interference Removal;185
6.1.2.1;7.2.1 Full-Duplex Transceivers with Hardware Impairments;188
6.1.2.2;7.2.2 Nonlinear Power Amplifier;189
6.1.2.3;7.2.3 I/Q Imbalance and Optimization of the Power Amplifier Operation Point;192
6.1.2.4;7.2.4 Influence of Impairments in the System Performance;195
6.1.3;7.3 ADC Resolution Requirements;196
6.1.4;7.4 Energy Efficiency and Spectral Efficiency;199
6.1.5;7.5 Summary of the Key Points;201
6.1.6;References;202
6.2;8 Massive MIMO Systems;205
6.2.1;8.1 Introduction;205
6.2.2;8.2 Single-Cell Massive MIMO System;206
6.2.2.1;8.2.1 Downlink;207
6.2.2.1.1;8.2.1.1 Precoding Techniques;207
6.2.2.2;8.2.2 Uplink;209
6.2.3;8.3 Precoding/Decoding Techniques with Imperfect Channel State Information;209
6.2.3.1;8.3.1 Channel Non-reciprocity and Antenna Coupling;210
6.2.3.2;8.3.2 Channel Estimation and Pilot Contamination;213
6.2.4;8.4 RF Front-End Minimum Requirements;215
6.2.4.1;8.4.1 Low-Resolution ADCs;216
6.2.4.2;8.4.2 Performance Evaluation of a MaMIMO Uplink with Low-Resolution ADC;218
6.2.5;8.5 Power Consumption Analysis;220
6.2.6;8.6 Summary of the Key Points;226
6.2.7;References;226
6.3;9 Internet of Things;229
6.3.1;9.1 IoT Applications and Challenges;229
6.3.2;9.2 IoT Proprietary and/or Licensed Solutions;231
6.3.2.1;9.2.1 Coverage and Capacity: Shannon and Transmission Bandwidth;236
6.3.2.2;9.2.2 Maximum Coupling Loss and Maximum Path Loss;238
6.3.3;9.3 NB-IoT: PHY and MAC Characteristics;240
6.3.3.1;9.3.1 Signals and Channels;242
6.3.3.2;9.3.2 State Model;243
6.3.3.3;9.3.3 Coverage, Efficiency, Capacity, Cost;246
6.3.4;9.4 LTE and NB-IoT Coexistence: Interference Due to RF Impairments;249
6.3.4.1;9.4.1 Modeling Signals and Interference;250
6.3.4.2;9.4.2 Numerical Results;252
6.3.5;9.5 Summary of the Key Points;254
6.3.6;References;255
6.4;10 Final Notes and Novel Issues;258
6.4.1;10.1 5G Implementation Challenges;258
6.4.1.1;10.1.1 The Combination of Massive MIMO and Full-Duplex;258
6.4.1.2;10.1.2 Millimeter Wave Wireless Communications;261
6.4.1.3;10.1.3 Massive MIMO Challenges;263
6.4.2;10.2 Summary of the Book;264
6.4.3;References;265
7;Index;266