Electromagnetic Interference and Compatibility

Recent progress in the fields of Electrical and Electronic Engineering has created new application scenarios and new Electromagnetic Compatibility (EMC) challenges, along with novel tools and methodologies to address them. This volume, which collects the contributions published in the “Electromagnetic Interference and Compatibility” Special Issue of MDPI Electronics, provides a vivid picture of current research trends and new developments in the rapidly evolving, broad area of EMC, including contributions on EMC issues in digital communications, power electronics, and analog integrated circuits and sensors, along with signal and power integrity and electromagnetic interference (EMI) suppression properties of materials

Solid State Circuits Technologies

The evolution of solid-state circuit technology has a long history within a relatively short period of time. This technology has lead to the modern information society that connects us and tools, a large market, and many types of products and applications. The solid-state circuit technology continuously evolves via breakthroughs and improvements every year. This book is devoted to review and present novel approaches for some of the main issues involved in this exciting and vigorous technology. The book is composed of 22 chapters, written by authors coming from 30 different institutions located in 12 different countries throughout the Americas, Asia and Europe. Thus, reflecting the wide international contribution to the book. The broad range of subjects presented in the book offers a general overview of the main issues in modern solid-state circuit technology. Furthermore, the book offers an in depth analysis on specific subjects for specialists. We believe the book is of great scientific and educational value for many readers. I am profoundly indebted to the support provided by all of those involved in the work. First and foremost I would like to acknowledge and thank the authors who worked hard and generously agreed to share their results and knowledge. Second I would like to express my gratitude to the Intech team that invited me to edit the book and give me their full support and a fruitful experience while working together to combine this book

Feasibility of Geiger-mode avalanche photodiodes in CMOS standard technologies for tracker detectors

The next generation of particle colliders will be characterized by linear lepton colliders, where the collisions between electrons and positrons will allow to study in great detail the new particle discovered at CERN in 2012 (presumably the Higgs boson). At present time, there are two alternative projects underway, namely the ILC (International Linear Collider) and CLIC (Compact LInear Collider). From the detector point of view, the physics aims at these particle colliders impose such extreme requirements, that there is no sensor technology available in the market that can fulfill all of them. As a result, several new detector systems are being developed in parallel with the accelerator. This thesis presents the development of a GAPD (Geiger-mode Avalanche PhotoDiode) pixel detector aimed mostly at particle tracking at future linear colliders. GAPDs offer outstanding qualities to meet the challenging requirements of ILC and CLIC, such as an extraordinary high sensitivity, virtually infinite gain and ultra-fast response time, apart from compatibility with standard CMOS technologies. In particular, GAPD detectors enable the direct conversion of a single particle event onto a CMOS digital pulse in the sub-nanosecond time scale without the utilization of either preamplifiers or pulse shapers. As a result, GAPDs can be read out after each single bunch crossing, a unique quality that none of its competitors can offer at the moment. In spite of all these advantages, GAPD detectors suffer from two main problems. On the one side, there exist noise phenomena inherent to the sensor, which induce noise pulses that cannot be distinguished from real particle events and also worsen the detector occupancy to unacceptable levels. On the other side, the fill-factor is too low and gives rise to a reduced detection efficiency. Solutions to the two problems commented that are compliant with the severe specifications of the next generation of particle colliders have been thoroughly investigated. The design and characterization of several single pixels and small arrays that incorporate some elements to reduce the intrinsic noise generated by the sensor are presented. The sensors and the readout circuits have been monolithically integrated in a conventional HV-CMOS 0.35 μm process. Concerning the readout circuits, both voltage-mode and current-mode options have been considered. Moreover, the time-gated operation has also been explored as an alternative to reduce the detected sensor noise. The design and thorough characterization of a prototype GAPD array, also monolithically integrated in a conventional 0.35 μm HV-CMOS process, is presented in the thesis as well. The detector consists of 10 rows x 43 columns of pixels, with a total sensitive area of 1 mm x 1 mm. The array is operated in a time-gated mode and read out sequentially by rows. The efficiency of the proposed technique to reduce the detected noise is shown with a wide variety of measurements. Further improved results are obtained with the reduction of the working temperature. Finally, the suitability of the proposed detector array for particle detection is shown with the results of a beam-test campaign conducted at CERN-SPS (European Organization for Nuclear Research-Super Proton Synchrotron). Apart from that, a series of additional approaches to improve the performance of the GAPD technology are proposed. The benefits of integrating a GAPD pixel array in a 3D process in terms of overcoming the fill-factor limitation are examined first. The design of a GAPD detector in the Global Foundries 130 nm/Tezzaron 3D process is also presented. Moreover, the possibility to obtain better results in light detection applications by means of the time-gated operation or correction techniques is analyzed too.Aquesta tesi presenta el desenvolupament d’un detector de píxels de GAPDs (Geiger-mode Avalanche PhotoDiodes) dedicat principalment a rastrejar partícules en futurs col•lisionadors lineals. Els GAPDs ofereixen unes qualitats extraordinàries per satisfer els requisits extremadament exigents d’ILC (International Linear Collider) i CLIC (Compact LInear Collider), els dos projectes per la propera generació de col•lisionadors que s’han proposat fins a dia d’avui. Entre aquestes qualitats es troben una sensibilitat extremadament elevada, un guany virtualment infinit i una resposta molt ràpida, a part de ser compatibles amb les tecnologies CMOS estàndard. En concret, els detectors de GAPDs fan possible la conversió directa d’un esdeveniment generat per una sola partícula en un senyal CMOS digital amb un temps inferior al nanosegon. Com a resultat d’aquest fet, els GAPDs poden ser llegits després de cada bunch crossing (la col•lisió de les partícules), una qualitat única que cap dels seus competidors pot oferir en el moment actual. Malgrat tots aquests avantatges, els detectors de GAPDs pateixen dos grans problemes. D’una banda, existeixen fenòmens de soroll inherents al sensor, els quals indueixen polsos de soroll que no poden ser distingits dels esdeveniments reals generats per partícules i que a més empitjoren l’ocupació del detector a nivells inacceptables. D’altra banda, el fill-factor (és a dir, l’àrea sensible respecte l’àrea total) és molt baix i redueix l’eficiència detectora. En aquesta tesi s’han investigat solucions als dos problemes comentats i que a més compleixen amb les especificacions altament severes dels futurs col•lisionadors lineals. El detector de píxels de GAPDs, el qual ha estat monolíticament integrat en un procés HV-CMOS estàndard de 0.35 μm, incorpora circuits de lectura en mode voltatge que permeten operar el sensor en l’anomenat mode time-gated per tal de reduir el soroll detectat. L’eficiència de la tècnica proposada queda demostrada amb la gran varietat d’experiments que s’han dut a terme. Els resultats del beam-test dut a terme al CERN indiquen la capacitat del detector de píxels de GAPDs per detectar partícules altament energètiques. A banda d’això, també s’han estudiat els beneficis d’integrar un detector de píxels de GAPDs en un procés 3D per tal d’incrementar el fill-factor. L’anàlisi realitzat conclou que es poden assolir fill-factors superiors al 90%

Crosstalk computing: circuit techniques, implementation and potential applications

Title from PDF of title [age viewed January 32, 2022Dissertation advisor: Mostafizur RahmanVitaIncludes bibliographical references (page 117-136)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2020This work presents a radically new computing concept for digital Integrated Circuits (ICs), called Crosstalk Computing. The conventional CMOS scaling trend is facing device scaling limitations and interconnect bottleneck. The other primary concern of miniaturization of ICs is the signal-integrity issue due to Crosstalk, which is the unwanted interference of signals between neighboring metal lines. The Crosstalk is becoming inexorable with advancing technology nodes. Traditional computing circuits always tries to reduce this Crosstalk by applying various circuit and layout techniques. In contrast, this research develops novel circuit techniques that can leverage this detrimental effect and convert it astutely to a useful feature. The Crosstalk is engineered into a logic computation principle by leveraging deterministic signal interference for innovative circuit implementation. This research work presents a comprehensive circuit framework for Crosstalk Computing and derives all the key circuit elements that can enable this computing model. Along with regular digital logic circuits, it also presents a novel Polymorphic circuit approach unique to Crosstalk Computing. In Polymorphic circuits, the functionality of a circuit can be altered using a control variable. Owing to the multi-functional embodiment in polymorphic-circuits, they find many useful applications such as reconfigurable system design, resource sharing, hardware security, and fault-tolerant circuit design, etc. This dissertation shows a comprehensive list of polymorphic logic gate implementations, which were not reported previously in any other work. It also performs a comparison study between Crosstalk polymorphic circuits and existing polymorphic approaches, which are either inefficient due to custom non-linear circuit styles or propose exotic devices. The ability to design a wide range of polymorphic logic circuits (basic and complex logics) compact in design and minimal in transistor count is unique to Crosstalk Computing, which leads to benefits in the circuit density, power, and performance. The circuit simulation and characterization results show a 6x improvement in transistor count, 2x improvement in switching energy, and 1.5x improvement in performance compared to counterpart implementation in CMOS circuit style. Nevertheless, the Crosstalk circuits also face issues while cascading the circuits; this research analyzes all the problems and develops auxiliary circuit techniques to fix the problems. Moreover, it shows a module-level cascaded polymorphic circuit example, which also employs the auxiliary circuit techniques developed. For the very first time, it implements a proof-of-concept prototype Chip for Crosstalk Computing at TSMC 65nm technology and demonstrates experimental evidence for runtime reconfiguration of the polymorphic circuit. The dissertation also explores the application potentials for Crosstalk Computing circuits. Finally, the future work section discusses the Electronic Design Automation (EDA) challenges and proposes an appropriate design flow; besides, it also discusses ideas for the efficient implementation of Crosstalk Computing structures. Thus, further research and development to realize efficient Crosstalk Computing structures can leverage the comprehensive circuit framework developed in this research and offer transformative benefits for the semiconductor industry.Introduction and Motivation -- More Moore and Relevant Beyond CMOS Research Directions -- Crosstalk Computing -- Crosstalk Circuits Based on Perception Model -- Crosstalk Circuit Types -- Cascading Circuit Issues and Sollutions -- Existing Polymorphic Circuit Approaches -- Crosstalk Polymorphic Circuits -- Comparison and Benchmarking of Crosstalk Gates -- Practical Realization of Crosstalk Gates -- Poential Applications -- Conclusion and Future Wor

Reconfigurable Receiver Front-Ends for Advanced Telecommunication Technologies

The exponential growth of converging technologies, including augmented reality, autonomous vehicles, machine-to-machine and machine-to-human interactions, biomedical and environmental sensory systems, and artificial intelligence, is driving the need for robust infrastructural systems capable of handling vast data volumes between end users and service providers. This demand has prompted a significant evolution in wireless communication, with 5G and subsequent generations requiring exponentially improved spectral and energy efficiency compared to their predecessors. Achieving this entails intricate strategies such as advanced digital modulations, broader channel bandwidths, complex spectrum sharing, and carrier aggregation scenarios. A particularly challenging aspect arises in the form of non-contiguous aggregation of up to six carrier components across the frequency range 1 (FR1). This necessitates receiver front-ends to effectively reject out-of-band (OOB) interferences while maintaining high-performance in-band (IB) operation. Reconfigurability becomes pivotal in such dynamic environments, where frequency resource allocation, signal strength, and interference levels continuously change. Software-defined radios (SDRs) and cognitive radios (CRs) emerge as solutions, with direct RF-sampling receivers offering a suitable architecture in which the frequency translation is entirely performed in digital domain to avoid analog mixing issues. Moreover, direct RF- sampling receivers facilitate spectrum observation, which is crucial to identify free zones, and detect interferences. Acoustic and distributed filters offer impressive dynamic range and sharp roll off characteristics, but their bulkiness and lack of electronic adjustment capabilities limit their practicality. Active filters, on the other hand, present opportunities for integration in advanced CMOS technology, addressing size constraints and providing versatile programmability. However, concerns about power consumption, noise generation, and linearity in active filters require careful consideration.This thesis primarily focuses on the design and implementation of a low-voltage, low-power RFFE tailored for direct sampling receivers in 5G FR1 applications. The RFFE consists of a balun low-noise amplifier (LNA), a Q-enhanced filter, and a programmable gain amplifier (PGA). The balun-LNA employs noise cancellation, current reuse, and gm boosting for wideband gain and input impedance matching. Leveraging FD-SOI technology allows for programmable gain and linearity via body biasing. The LNA's operational state ranges between high-performance and high-tolerance modes, which are apt for sensitivityand blocking tests, respectively. The Q-enhanced filter adopts noise-cancelling, current-reuse, and programmable Gm-cells to realize a fourth-order response using two resonators. The fourth-order filter response is achieved by subtracting the individual response of these resonators. Compared to cascaded and magnetically coupled fourth-order filters, this technique maintains the large dynamic range of second-order resonators. Fabricated in 22-nm FD-SOI technology, the RFFE achieves 1%-40% fractional bandwidth (FBW) adjustability from 1.7 GHz to 6.4 GHz, 4.6 dB noise figure (NF) and an OOB third-order intermodulation intercept point (IIP3) of 22 dBm. Furthermore, concerning the implementation uncertainties and potential variations of temperature and supply voltage, design margins have been considered and a hybrid calibration scheme is introduced. A combination of on-chip and off-chip calibration based on noise response is employed to effectively adjust the quality factors, Gm-cells, and resonance frequencies, ensuring desired bandpass response. To optimize and accelerate the calibration process, a reinforcement learning (RL) agent is used.Anticipating future trends, the concept of the Q-enhanced filter extends to a multiple-mode filter for 6G upper mid-band applications. Covering the frequency range from 8 to 20 GHz, this RFFE can be configured as a fourth-order dual-band filter, two bandpass filters (BPFs) with an OOB notch, or a BPF with an IB notch. In cognitive radios, the filter’s transmission zeros can be positioned with respect to the carrier frequencies of interfering signals to yield over 50 dB blocker rejection

Learning-Based Hardware Design for Data Acquisition Systems

This multidisciplinary research work aims to investigate the optimized information extraction from signals or data volumes and to develop tailored hardware implementations that trade-off the complexity of data acquisition with that of data processing, conceptually allowing radically new device designs. The mathematical results in classical Compressive Sampling (CS) support the paradigm of Analog-to-Information Conversion (AIC) as a replacement for conventional ADC technologies. The AICs simultaneously perform data acquisition and compression, seeking to directly sample signals for achieving specific tasks as opposed to acquiring a full signal only at the Nyquist rate to throw most of it away via compression. Our contention is that in order for CS to live up its name, both theory and practice must leverage concepts from learning. This work demonstrates our contention in hardware prototypes, with key trade-offs, for two different fields of application as edge and big-data computing. In the framework of edge-data computing, such as wearable and implantable ecosystems, the power budget is defined by the battery capacity, which generally limits the device performance and usability. This is more evident in very challenging field, such as medical monitoring, where high performance requirements are necessary for the device to process the information with high accuracy. Furthermore, in applications like implantable medical monitoring, the system performances have to merge the small area as well as the low-power requirements, in order to facilitate the implant bio-compatibility, avoiding the rejection from the human body. Based on our new mathematical foundations, we built different prototypes to get a neural signal acquisition chip that not only rigorously trades off its area, energy consumption, and the quality of its signal output, but also significantly outperforms the state-of-the-art in all aspects. In the framework of big-data and high-performance computation, such as in high-end servers application, the RF circuits meant to transmit data from chip-to-chip or chip-to-memory are defined by low power requirements, since the heat generated by the integrated circuits is partially distributed by the chip package. Hence, the overall system power budget is defined by its affordable cooling capacity. For this reason, application specific architectures and innovative techniques are used for low-power implementation. In this work, we have developed a single-ended multi-lane receiver for high speed I/O link in servers application. The receiver operates at 7 Gbps by learning inter-symbol interference and electromagnetic coupling noise in chip-to-chip communication systems. A learning-based approach allows a versatile receiver circuit which not only copes with large channel attenuation but also implements novel crosstalk reduction techniques, to allow single-ended multiple lines transmission, without sacrificing its overall bandwidth for a given area within the interconnect's data-path

New Architectures and Circuits for Pushing the Dynamic Range and Multiplexing Boundaries of CMOS-Integrated Sensors

Over the last decades, CMOS-integrated sensors have made impressive progress in performance, form-factor, and energy-efficiency for various applications such as imaging, physical/chemical sensing, bio/health monitoring. In the era of the artificial intelligence (AI) and the internet-of-things (IoT), such CMOS-integrated sensors are essential for massive and comprehensive data acquisition, where sensing range (or dynamic range), signal fidelity (or signal-to-noise ratio), and data throughput are key factors. Towards pushing the boundaries of such sensing capabilities, in this dissertation, novel sensing architectures are presented with energy/area-efficient circuit design techniques for multi-channel CMOS optical sensors and neural interfaces. The first topic is a fully-integrated, wide linear dynamic range optical sensor array combining linear and single-photon avalanche diode operation within each pixel. A pulse-counting readout scheme provides in-pixel digitization in an area-efficient manner for both operation modes, enabling fully parallel measurement across the array. The proposed dual-mode optical sensor array alternately requires high-voltage(10-20 V) and low-voltage supply (2-5 V) for reverse bias of the photodiodes, which is provided by a reconfigurable, closed-loop high-voltage charge pump in the same substrate. An 8 x 8 array architecture along with the dual-mode bias generator is fabricated in a general purpose 180 nm CMOS process and demonstrates 129 dB dynamic range while maintaining linear photoresponse operating with a dual-mode frame rate of 20 Hz. The second topic is a new approach for applying code-division multiplexing (CDM) to current-mode and voltage-mode sensor arrays with analog-domain orthogonal encoding directly in a shared, single analog-front-end circuit, which enables simultaneous readout for multiple sensors. The approach is applied to a 8 x 16 array of CMOS-integrated photodetectors and implemented in a general purpose 180 nm CMOS process, where the 16 channel CDM-based oversampling readout achieves an SNR improvement of more than 12 dB compared with time-division multiplexing at the same sampling rate. In addition, a CDM-based neural recording architecture is presented, which offers a significant tolerance to interference that can be injected through long cables

VLSI Circuits for Bidirectional Neural Interfaces

Medical devices that deliver electrical stimulation to neural tissue are important clinical tools that can augment or replace pharmacological therapies. The success of such devices has led to an explosion of interest in the field, termed neuromodulation, with a diverse set of disorders being targeted for device-based treatment. Nevertheless, a large degree of uncertainty surrounds how and why these devices are effective. This uncertainty limits the ability to optimize therapy and gives rise to deleterious side effects. An emerging approach to improve neuromodulation efficacy and to better understand its mechanisms is to record bioelectric activity during stimulation. Understanding how stimulation affects electrophysiology can provide insights into disease, and also provides a feedback signal to autonomously tune stimulation parameters to improve efficacy or decrease side-effects. The aims of this work were taken up to advance the state-of-the-art in neuro-interface technology to enable closed-loop neuromodulation therapies. Long term monitoring of neuronal activity in awake and behaving subjects can provide critical insights into brain dynamics that can inform system-level design of closed-loop neuromodulation systems. Thus, first we designed a system that wirelessly telemetered electrocorticography signals from awake-behaving rats. We hypothesized that such a system could be useful for detecting sporadic but clinically relevant electrophysiological events. In an 18-hour, overnight recording, seizure activity was detected in a pre-clinical rodent model of global ischemic brain injury. We subsequently turned to the design of neurostimulation circuits. Three critical features of neurostimulation devices are safety, programmability, and specificity. We conceived and implemented a neurostimulator architecture that utilizes a compact on-chip circuit for charge balancing (safety), digital-to-analog converter calibration (programmability) and current steering (specificity). Charge balancing accuracy was measured at better than 0.3%, the digital-to-analog converters achieved 8-bit resolution, and physiological effects of current steering stimulation were demonstrated in an anesthetized rat. Lastly, to implement a bidirectional neural interface, both the recording and stimulation circuits were fabricated on a single chip. In doing so, we implemented a low noise, ultra-low power recording front end with a high dynamic range. The recording circuits achieved a signal-to-noise ratio of 58 dB and a spurious-free dynamic range of better than 70 dB, while consuming 5.5 μW per channel. We demonstrated bidirectional operation of the chip by recording cardiac modulation induced through vagus nerve stimulation, and demonstrated closed-loop control of cardiac rhythm

Nano-Watt Modular Integrated Circuits for Wireless Neural Interface.

In this work, a nano-watt modular neural interface circuit is proposed for ECoG neuroprosthetics. The main purposes of this work are threefold: (1) optimizing the power-performance of the neural interface circuits based on ECoG signal characteristics, (2) equipping a stimulation capability, and (3) providing a modular system solution to expand functionality. To achieve these aims, the proposed system introduces the following contributions/innovations: (1) power-noise optimization based on the ECoG signal driven analysis, (2) extreme low-power analog front-ends, (3) Manchester clock-edge modulation clock data recovery, (4) power-efficient data compression, (5) integrated stimulator with fully programmable waveform, (6) wireless signal transmission through skin, and (7) modular expandable design. Towards these challenges and contributions, three different ECoG neural interface systems, ENI-1, ENI-16, and ENI-32, have been designed, fabricated, and tested. The first ENI system(ENI-1) is a one-channel analog front-end and fabricated in a 0.25µm CMOS process with chopper stabilized pseudo open-loop preamplifier and area-efficient SAR ADC. The measured channel power, noise and area are 1.68µW at 2.5V power-supply, 1.69µVrms (NEF=2.43), and 0.0694mm^2, respectively. The fabricated IC is packaged with customized miniaturized package. In-vivo human EEG is successfully measured with the fabricated ENI-1-IC. To demonstrate a system expandability and wireless link, ENI-16 IC is fabricated in 0.25µm CMOS process and has sixteen channels with a push-pull preamplifier, asynchronous SAR ADC, and intra-skin communication(ISCOM) which is a new way of transmitting the signal through skin. The measured channel power, noise and area are 780nW, 4.26µVrms (NEF=5.2), and 2.88mm^2, respectively. With the fabricated ENI-16-IC, in-vivo epidural ECoG from monkey is successfully measured. As a closed-loop system, ENI-32 focuses on optimizing the power performance based on a bio-signal property and integrating stimulator. ENI-32 is fabricated in 0.18µm CMOS process and has thirty-two recording channels and four stimulation channels with a cyclic preamplifier, data compression, asymmetric wireless transceiver (Tx/Rx). The measured channel power, noise and area are 140nW (680nW including ISCOM), 3.26µVrms (NEF=1.6), and 5.76mm^2, respectively. The ENI-32 achieves an order of magnitude power reduction while maintaining the system performance. The proposed nano-watt ENI-32 can be the first practical wireless closed-loop solution with a practically miniaturized implantable device.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/98064/1/schang_1.pd

Development, Optimisation and Characterisation of a Radiation Hard Mixed-Signal Readout Chip for LHCb

The Beetle chip is a radiation hard, 128 channel pipelined readout chip for silicon strip detectors. The front-end consists of a charge-sensitive preamplifier followed by a CR-RC pulse shaper. The analogue pipeline memory is implemented as a switched capacitor array with a maximum latency of 4us. The 128 analogue channels are multiplexed and transmitted off chip in 900ns via four current output drivers. Beside the pipelined readout path, the Beetle provides a fast discrimination of the front-end pulse. Within this doctoral thesis parts of the radiation hard Beetle readout chip for the LHCb experiment have been developed. The overall chip performances like noise, power consumption, input charge rates have been optimised as well as the elimination of failures so that the Beetle fulfils the requirements of the experiment. Furthermore the characterisation of the chip was a major part of this thesis. Beside the detailed measurement of the chip performance, several irradiation tests and an Single Event Upset (SEU) test were performed. A long-time measurement with a silicon strip detector was also part of this work as well as the development and test of a first mass production test setup. The Beetle chip showed no functional failure and only slight degradation in the analogue performance under irradiation of up to 130Mrad total dose. The Beetle chip fulfils all requirements of the vertex detector (VELO), the trigger tracker (TT) and the inner tracker (IT) and is ready for the start of LHCb end of 2007