Modular Nonlinear Characterization System and Large-Signal Behavioral Modelling of Unmatched Transistors for Streamlined Power Amplifier Design

This thesis provides a comprehensive approach to the characterization and modelling of large-signal nonlinear RF/microwave devices, circuits and systems. This research is moti- vated by the increased linearity and power-efficiency requirements of modern power ampli- fier technology for wireless communications. For instance, maximizing the power amplifier’s efficiency can only be achieved by operating RF transistors under strong nonlinear condi- tions, however this is contradictory to maximizing PA linearity. Simultaneously designing for efficiency and linearity is a challenging trade-off in today’s fragmented design process, therefore the advancement of computer-aided design (CAD) tools is essential for achieving an optimal solution. The successful and effective CAD tool based PA design relies on the availability of accurate nonlinear models to mimic the electro-thermal behaviour of RF transistors. The accuracy of these models depends on three factors: 1. The formulation of the model. 2. The model extraction procedure. 3. The accuracy of the measurement data. While prior work focuses separately on the improved model formulations or improving characterization accuracy, this thesis provides a comprehensive analysis of all three factors. This thesis proposes a modular large-signal RF device characterization system, and a non- linear behavioral model capable of handling strongly nonlinear unmatched RF transistors, each necessary to streamline the design process and achieve a first-pass PA design. iii As a first step, a large-signal characterization system has been developed to measure the multi-harmonic frequency response of RF transistors and has the ability to i) Perform high-power measurements, ii) Characterize unmatched transistors, iii) Operate the DUT under any possible operating condition, iv) Synthesize any multi-harmonic stimulus, and v) Reconstruct the time-domain I/V waveforms at the ports of the DUT. The proposed characterization system eliminates fragmentation between measurement and simulation environments by providing seamless integration with Harmonic Balance simulations. This provides a common framework that integrates all steps of the PA design process from device-level characterization, to circuit-level measurement and validation. This system is implemented using modular instruments consisting of mixer-based receivers, arbitrary waveform generators, impedance tuners, and a multi-harmonic phase-coherent reference source. It also integrates sequential calibration routines to provide receiver, port match, and source-power corrections to the DUT measurement plane and measurement routines for automated data collection. The second part of the thesis researches black-box frequency-domain behavioral mod- els that can approximate strongly nonlinear, unmatched devices. Our investigation yielded two complimentary solutions to ensure the targeted modelling accuracy. First, improving the accuracy of a first-order expansion-based Poly-Harmonic Distortion (PHD) model by 5dB, in terms of Normalized Mean-Squared Error (NMSE), by minimizing multi-harmonic reflections that artificially increase the order of the nonlinear system. While this addresses the fictitious need for higher-order models due to the deficiencies in the model extraction procedure, strongly nonlinear devices will require high-order models to achieve the targeted accuracy over a larger measurement distribution. Hence, a variable order Multi-Harmonic Volterra (MHV) model is proposed to extend the PHD model formulation to strong non- linear devices. This model is extracted by utilizing the proposed characterization system to extract higher-order multi-variate model coefficients not included in the PHD model. The resulting model improves DC drain current prediction by 5dB and improves funda- mental output-power prediction by 2dB. The MHV model improves the vector power-gain prediction by 3.4dB in realistic PA design applications, thereby providing better emulation of linearization techniques within a simulation environment. Finally, a concurrent dual-band PA design is studied as an example of how the pro- iv posed nonlinear characterization system and behavioural modelling approach can be used to enable complex PA designs. First, a 10W Class-AB PA is designed using dual-band matching-network theory, however it is difficult to implement because the design technique does not control the matching fractional bandwidth as a design parameter. Therefore, an alternative Class-J 45W dual-band PA was designed using a low-impedance matching network, combined with a trans-impedance dual-band filter. Although the dual-band PA can achieve comparable performance to an equivalent single-band PA at each separate fre- quency, further development of characterization, modeling, and circuit design techniques is needed to achieve high-efficiency during concurrent operation

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

SMARAD - Centre of Excellence in Smart Radios and Wireless Research - Activity Report 2008 - 2010

Centre of Excellence in Smart Radios and Wireless Research (SMARAD), originally established with the name Smart and Novel Radios Research Unit, is aiming at world-class research and education in Future radio and antenna systems, Cognitive radio, Millimetre wave and THz techniques, Sensors, and Materials and energy, using its expertise in RF, microwave and millimetre wave engineering, in integrated circuit design for multi-standard radios as well as in wireless communications. SMARAD has the Centre of Excellence in Research status from the Academy of Finland since 2002 (2002-2007 and 2008-2013). Currently SMARAD consists of five research groups from three departments, namely the Department of Radio Science and Engineering, Department of Micro and Nanosciences, and Department of Signal Processing and Acoustics, all within the Aalto University School of Electrical Engineering. The total number of employees within the research unit is about 100 including 8 professors, about 30 senior scientists and about 40 graduate students and several undergraduate students working on their Master thesis. The relevance of SMARAD to the Finnish society is very high considering the high national income from exports of telecommunications and electronics products. The unit conducts basic research but at the same time maintains close co-operation with industry. Novel ideas are applied in design of new communication circuits and platforms, transmission techniques and antenna structures. SMARAD has a well-established network of co-operating partners in industry, research institutes and academia worldwide. It coordinates a few EU projects. The funding sources of SMARAD are diverse including the Academy of Finland, EU, ESA, Tekes, and Finnish and foreign telecommunications and semiconductor industry. As a byproduct of this research SMARAD provides highest-level education and supervision to graduate students in the areas of radio engineering, circuit design and communications through Aalto University and Finnish graduate schools such as Graduate School in Electronics, Telecommunications and Automation (GETA). During years 2008 – 2010, 21 doctor degrees were awarded to the students of SMARAD. In the same period, the SMARAD researchers published 141 refereed journal articles and 333 conference papers

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Hardware emulation of wireless communication fading channels

This dissertation investigates several main challenges to implementing hardware-based wireless fading channel emulators with emphasis on incorporating accurate correlation properties. Multiple-input multiple-output (MIMO) fading channels are usually triply-selective with three types of correlation: temporal correlation, inter-tap correlation, and spatial correlation. The proposed emulators implement the triply-selective fading Channel Impulse Response (CIR) by incorporating the three types of correlation into multiple uncorrelated frequency-flat Rayleigh fading waveforms while meeting real-time requirements for high data-rate, large-sized MIMO, and/or long CIR channels. Specifically, mixed parallel-serial computational structures are implemented for Kronecker products of the correlation matrices, which makes the best tradeoff between computational speed and hardware usage. Five practical fading channel examples are implemented for RF or underwater acoustic MIMO applications. The performance of the hardware emulators are verified with an Altera Field-Programmable Gate Array (FPGA) platform and the results match the software simulators in terms of statistical and correlation properties. The dissertation also contributes to the development of a 2-by-2 MIMO transceiver testbench that is used to measure real-world fading channels. Intensive channel measurements are performed for indoor fixed mobile-to-mobile channels and the estimated CIRs demonstrate the triply-selective correlation properties --Abstract, page iv

Proceedings of the 35th WIC Symposium on Information Theory in the Benelux and the 4th joint WIC/IEEE Symposium on Information Theory and Signal Processing in the Benelux, Eindhoven, the Netherlands May 12-13, 2014

Compressive sensing (CS) as an approach for data acquisition has recently received much attention. In CS, the signal recovery problem from the observed data requires the solution of a sparse vector from an underdetermined system of equations. The underlying sparse signal recovery problem is quite general with many applications and is the focus of this talk. The main emphasis will be on Bayesian approaches for sparse signal recovery. We will examine sparse priors such as the super-Gaussian and student-t priors and appropriate MAP estimation methods. In particular, re-weighted l2 and re-weighted l1 methods developed to solve the optimization problem will be discussed. The talk will also examine a hierarchical Bayesian framework and then study in detail an empirical Bayesian method, the Sparse Bayesian Learning (SBL) method. If time permits, we will also discuss Bayesian methods for sparse recovery problems with structure; Intra-vector correlation in the context of the block sparse model and inter-vector correlation in the context of the multiple measurement vector problem

The University Defence Research Collaboration In Signal Processing

This chapter describes the development of algorithms for automatic detection of anomalies from multi-dimensional, undersampled and incomplete datasets. The challenge in this work is to identify and classify behaviours as normal or abnormal, safe or threatening, from an irregular and often heterogeneous sensor network. Many defence and civilian applications can be modelled as complex networks of interconnected nodes with unknown or uncertain spatio-temporal relations. The behavior of such heterogeneous networks can exhibit dynamic properties, reflecting evolution in both network structure (new nodes appearing and existing nodes disappearing), as well as inter-node relations. The UDRC work has addressed not only the detection of anomalies, but also the identification of their nature and their statistical characteristics. Normal patterns and changes in behavior have been incorporated to provide an acceptable balance between true positive rate, false positive rate, performance and computational cost. Data quality measures have been used to ensure the models of normality are not corrupted by unreliable and ambiguous data. The context for the activity of each node in complex networks offers an even more efficient anomaly detection mechanism. This has allowed the development of efficient approaches which not only detect anomalies but which also go on to classify their behaviour

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering