2020 IEEE Radio & Wireless Week

Abstract

Efficiency and linearity are key features in every communication system. In a typical transmit-receive module, the PA consumes around 70% of the total energy and, being the last stage of the transmitter, it is the main responsible for the overall system linearity. However, efficiency and linearity are contrasting features, more still in applications that make use of spectrum-efficient digital modulation schemes, such as 5G systems or new high throughput satellites. The ability of the Doherty architecture of operating at high efficiency at significant output power back-off has led the RF and microwave community to re-discover the Doherty concept and adapt it to the requirements of modern high frequency transmitters both for terrestrial and space applications. Moreover, its implementation on GaN technology has the potentials to offer game-changing advantage. This workshop aims to present recent progress on integrated Doherty Amplifiers and all the aspects related to their implementation, covering state-of-the-art GaN technology, advanced experimental characterization techniques at device/ circuit level, as well as various Doherty HPA MMIC implementations. Talks and Speakers: Integrated Doherty Power Amplifiers: Challenges and Solutions Anna Piacibello, Vittorio Camarchia, Politecnico di Torino GaN Enabling Technologies Remy Leblanc, OMMIC Foundry Load Pull Characterisation Oriented to the Design of Doherty Power Amplifiers Roberto Quaglia, Cardiff University High Power Amplifications and Integration Challenges of Active Antennas for Satellite Communication Václav Valenta, European Space Agency Design of MMIC Doherty Amplifier: Standard vs. Stacked Architecture Ferdinando Costanzo, Rocco Giofrè, Paolo Colantonio, University of Roma Tor Vergata Design of MMIC Doherty Amplifier: Multi-Doherty Approach Anna Piacibello, Vittorio Camarchia, University of Roma Tor Vergata Linearity Assessment Techniques for GaN MMICs PAs: Simulations & Experimental Characterization Nuno Borges Carvalho, University of Aveiro Workshop Solid State Power Amplification for SpaceBorne Systems Room: Bonham C Workshop Advances in SiGe BiCMOS and RF-CMOS Frontend Technologies Room: Bonham D Workshop Machine Learning and Dimensionality Reduction Techniques for RF Components and Systems: from Modeling to Linearization Room: Bonham E Organizers: Tomas Gotthans, Brno University of Technology Genevieve Baudoin, Université Paris-Est, ESIEE Paris Abstract: This workshop will review critical technologies, design challenges and recent trends in the area of space-borne solid-state high power amplification. Well established solutions for traditional RF payloads will be discussed as well as advanced techniques applied to multibeam direct radiating antennas. Systems and solutions covering frequency bands up to mm-waves will be discussed, with particular focus on high-efficiency concepts, thermal management, which are of prime importance in spaceborne systems. Advanced GaN MMIC technologies and trends will be reviewed together with the MMIC integration approaches for improved spacecraft efficiency. This workshop will review critical technologies, design challenges and recent trends in the area of space-borne solid-state high power amplification. Well established solutions for traditional RF payloads will be discussed as well as advanced techniques applied to multibeam direct radiating antennas. Systems and solutions covering frequency bands up to mm-waves will be discussed, with particular focus on high-efficiency concepts, thermal management, which are of prime importance in spaceborne systems. Advanced GaN MMIC technologies and trends will be reviewed together with the MMIC integration approaches for improved spacecraft efficiency. Talks and Speakers: Concepts and Challenges for High Power Amplification in Space Václav Valenta, European Space Agency Millimeter-wave Solid-State Power Amplifiers for Space Based Communications and Remote Sensing Naresh Deo, Quinstar Designing Microwave Power Amplifiers for Space Applications Howard Hausman, RF Microwave Consulting Services, Hofstra University GaN Technologies and Recent MMIC Results for Space Applications Stéphane Piotrowicz, III-V Labs GaN-on-Diamond MMICs for Space: A 2020 Status Report Felix Ejeckam, Akash Systems, Inc. Organizers: Ahmet Cagri Ulusoy, Karlsruher Institut für Technologie Vadim Issakov, University Magdeburg Abstract: This workshop will review recent advances on frontend technologies in SiGe BiCMOS and RF-CMOS, especially in the context of emerging and maturing millimeter-wave applications such 5G, beyond 5G, automotive radar and industrial sensors. This workshop will review recent advances on frontend technologies in SiGe BiCMOS and RF-CMOS, especially in the context of emerging and maturing millimeter-wave applications such 5G, beyond 5G, automotive radar and industrial sensors. Talks and Speakers: Multi-Band Millimeter-Wave Frontends in SiGe BiCMOS and RF-CMOS Ahmet Cagri Ulusoy, Karlsruher Institut für Technologie mm-Wave Transceiver for Radar Applications in Advanced SiGe BiCMOS and nano-scale CMOS Technologies Vadim Issakov, University Magdeburg Devices and Circuits for mm-Wave Radar in CMOS Krishnanshu Dandu, Texas Instruments Recent advances in high speed high bandwidth data converters at Teledyne e2v Romain Pilard, Teledyne e2v RF-SOI Technology for RF-CMOS Front End Modules Venkata Vanukuru, GlobalFoundries Millimeter Wave Power Amplifiers in Silicon: State of the Art and Future Technology Trend Hua Wang, Georgia Institute of Technology Organizers: Pere L. Gilabert, Universitat Politècnica de Catalunya Christian Fager, Chalmers University of Technology Abstract: This workshop aims to provide an updated overview of the use of machine learning algorithms for RF modeling at both device, circuit, and system level. At device level, artificial neural networks (ANNs) are used to characterize RF and microwave components, such as power transistors or RFIC passive components. At circuit and system level, this workshop will present some advanced solutions on ANN approaches to model and compensate for unwanted nonlinear effects in the transmitter chain. In particular, ANNs are used for power amplifier (PA) modeling, digital predistortion (DPD) linearization and IQ imbalance mitigation. In addition, feature selection and feature extraction techniques, used to reduce the number of parameters of parametric models as well as to ensure a proper well-conditioned estimation for related variables, will be discussed. This workshop aims to provide an updated overview of the use of machine learning algorithms for RF modeling at both device, circuit, and system level. At device level, artificial neural networks (ANNs) are used to characterize RF and microwave components, such as power transistors or RFIC passive components. At circuit and system level, this workshop will present some advanced solutions on ANN approaches to model and compensate for unwanted nonlinear effects in the transmitter chain. In particular, ANNs are used for power amplifier (PA) modeling, digital predistortion (DPD) linearization and IQ imbalance mitigation. In addition, feature selection and feature extraction techniques, used to reduce the number of parameters of parametric models as well as to ensure a proper well-conditioned estimation for related variables, will be discussed. Talks and Speakers: Artificial Neural Networks for Modeling Nonlinear Microwave Devices and Circuits Qi-Jun Zhang, Carleton University, Modeling RF Power Transistors Using Artificial Neural Networks Lei Zhang, NXP Modeling Nonlinearities Using Neural Networks – From Transistor Modeling to Power Amplifier Linearization Mohamed Helaoui, University of Calgary Artificial Neural Networks Based Digital Predistortion for Signal Quality Enhancement in MIMO/Multiband Transmitters Meenakshi Rawat, Indian Institute of Technology Roorkee Patric Roblin, Ohio State University Dimensionality Reduction Techniques for Digital Predistortion Linearization of High Efficient Power Amplifiers Pere L. Gilabert, Universitat Politècnica de Catalunya