Signal Processing Techniques for Power Efficient Wireless Communication Systems Practical Approaches for RF Impairments Reduction

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.

1. Introduction

      1.1.  Book motivation

      1.2.  Communication systems

      1.3.  Digital block description: Multicarrier modulation

      1.4.  RF front-end description

      1.5.  Interface: ADC and DAC

      1.6.  Implementation issues

      1.7.  Main contributions of this book

                1.7.2. Digital based RF compensation techniques: Implementation cost and energy saving effects

                1.7.3. RF imperfection on novel implementations: Massive MIMO, Full-duplex and IoT   nodes

      1.8.  Outline of this book

2. RF front-end imperfection models

2.1.  Power amplifiers: nonlinear distortion

2.2.  LNA and VGA

2.3.  Mixers: phase and amplitude imbalances

2.4.  Local oscillator: Phase noise

2.5.  ADC: quantization noise and nonlinear distortion

2.6.  DAC

3.1.  Digital block and front-end power consumption models

3.2.  ADC: power consumption, resolution and sampling frequency trade-off

3.3.  Short-range and long-range links

3.4.  Power consumption scaling

3.4.1. Bandwidth dependence

3.4.2. Number of antennas

3.4.3. Data rate (constellation size)

3.5.  Energy efficiency (EE)  and Spectral efficiency (SE): A case of study

4. Power amplifiers

4.1.  Operation point: power consumption vs distortion tradeoff

4.2.  Linearization techniques

4.2.1. Low power amplifiers

4.2.2. Median/high power amplifiers

4.3.  Figure of merit: total degradation and ACPR

5. ADC and DAC in multicarrier systems

5.1.  Architectures: Dynamic range, resolution, sampling frequency tradeoff

5.2.  Modeling and Compensation: Narrowband vs. broadband techniques

5.3.  Metrics and Figures of Merit

5.4.  Measurements.

6. Carrier frequency offset (CFO) and phase noise

6.1.  Effects of the CFO and phase noise in the system performance

6.2.  Critical applications: unstable oscillators and high speed vehicles

6.3.  Estimation techniques for the downlink (single user case)

6.4.  Estimation and compensation techniques for the uplink (multiuser case)

7. Full-duplex

7.1.  Introduction

7.2.  System model with RF imperfections

7.3.  ADC resolution requirements

7.4.  Self-interference removal

7.4.1. Phase noise effects  

7.4.2. Power amplifier operation point

7.5.  Energy efficiency and spectral efficiency

8. Massive MIMO

8.1.  Introduction      

8.2.  Model

8.3.  RF front-end minimum requirements

8.4.  Low-resolution ADC/DAC

8.5.  Power consumption analysis

8.5.1. Downlink EE

8.5.2. Uplink EE

9. Internet of things

9.1.  Introduction

9.2.  RF imperfections effects on power constrained devices

9.2.1. Power amplifiers distortion: Compensation feasibility

9.2.2. Carrier frequency offset and phase noise: low complexity compensation techniques

9.3. Power consumption and performance study.

9.4. Self-powered devices: Energy harvesting and wireless power transfer

10. Final notes and novel issues 

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.