Dependable Digitally-Assisted Mixed-Signal IPs Based on Integrated Self-Test & Self-Calibration

Heterogeneous SoC devices, including sensors, analogue and mixed-signal front-end circuits and the availability of massive digital processing capability, are being increasingly used in safety-critical applications like in the automotive, medical, and the security arena. Already a significant amount of attention has been paid in literature with respect to the dependability of the digital parts in heterogeneous SoCs. This is in contrast to especially the sensors and front-end mixed-signal electronics; these are however particular sensitive to external influences over time and hence determining their dependability. This paper provides an integrated SoC/IP approach to enhance the dependability. It will give an example of a digitally-assisted mixed-signal front-end IP which is being evaluated under its mission profile of an automotive tyre pressure monitoring system. It will be shown how internal monitoring and digitally-controlled adaptation by using embedded processors can help in terms of improving the dependability of this mixed-signal part under harsh conditions for a long time

Concepts for Short Range Millimeter-wave Miniaturized Radar Systems with Built-in Self-Test

This work explores short-range millimeter wave radar systems, with emphasis on miniaturization and overall system cost reduction. The designing and implementation processes, starting from the system level design considerations and characterization of the individual components to final implementation of the proposed architecture are described briefly. Several D-band radar systems are developed and their functionality and performances are demonstrated

Variable Spurious Noise Mitigation Techniques in Hysteretic Buck Converters

This work proposes a current-mode hysteretic buck converter with a spur-free constant-cycle frequency-hopping controller that fully eliminates spurs from the switching noise spectrum irrespective of variations in the switching frequency and operating conditions. As a result, the need for frequency regulation loops to ensure non-varying switching frequency (i.e. fixed spurs location) in hysteretic controllers is eliminated. Moreover, compared to frequency regulation loops, the proposed converter offers the advantage of eliminating mixing and interference altogether due to its spur-free operation, and thus, it can be used to power, or to be integrated within noise-sensitive systems while benefiting from the superior dynamic performance of its hysteretic operation. The proposed converter uses dual-sided hysteretic band modulation to eliminate the inductor current imbalance that results from frequency hopping along with the output voltage transients and low-frequency noise floor peaking associated with it. Moreover, a feedforward adaptive hysteretic band controller is proposed to reduce variations in the switching frequency with the input voltage, and an all-digital soft-startup circuit is proposed to control the in-rush current without requiring any off-chip components. The converter is implemented in a 0.35-õm standard CMOS technology and it achieves 92% peak efficiency

A 16-Channel Fully Configurable Neural SoC With 1.52 μW/Ch Signal Acquisition, 2.79 μW/Ch Real-Time Spike Classifier, and 1.79 TOPS/W Deep Neural Network Accelerator in 22 nm FDSOI

With the advent of high-density micro-electrodes arrays, developing neural probes satisfying the real-time and stringent power-efficiency requirements becomes more challenging. A smart neural probe is an essential device in future neuroscientific research and medical applications. To realize such devices, we present a 22 nm FDSOI SoC with complex on-chip real-time data processing and training for neural signal analysis. It consists of a digitally-assisted 16-channel analog front-end with 1.52 μ W/Ch, dedicated bio-processing accelerators for spike detection and classification with 2.79 μ W/Ch, and a 125 MHz RISC-V CPU, utilizing adaptive body biasing at 0.5 V with a supporting 1.79 TOPS/W MAC array. The proposed SoC shows a proof-of-concept of how to realize a high-level integration of various on-chip accelerators to satisfy the neural probe requirements for modern applications

Solutions pour l'auto-adaptation des systèmes sans fil

The current demand on ubiquitous connectivity imposes stringent requirements on the fabrication of Radio-Frequency (RF) circuits. Designs are consequently transferred to the most advanced CMOS technologies that were initially introduced to improve digital performance. In addition, as technology scales down, RF circuits are more and more susceptible to a lot of variations during their lifetime, as manufacturing process variability, temperature, environmental conditions, aging… As a result, the usual worst-case circuit design is leading to sub-optimal conditions, in terms of power and/or performance most of the time for the circuit. In order to counteract these variations, increasing the performances and also reduce power consumption, adaptation strategies must be put in place.More importantly, the fabrication process introduces more and more performance variability, which can have a dramatic impact on the fabrication yield. That is why RF designs are not easily fabricated in the most advanced CMOS technologies, as 32nm or 22nm nodes for instance. In this context, the performances of RF circuits need to be calibrated after fabrication so as to take these variations into account and recover yield loss.This thesis work is presenting on a post-fabrication calibration technique for RF circuits. This technique is performed during production testing with minimum extra cost, which is critical since the cost of test can be comparable to the cost of fabrication concerning RF circuits and cannot be further raised. Calibration is enabled by equipping the circuit with tuning knobs and sensors. Optimal tuning knob identification is achieved in one-shot based on a single test step that involves measuring the sensor outputs once. For this purpose, we rely on variation-aware sensors which provide measurements that remain invariant under tuning knob changes. As an auxiliary benefit, the variation-aware sensors are non-intrusive and totally transparent to the circuit.Our proposed methodology has first been demonstrated with simulation data with an RF power amplifier as a case study. Afterwards, a silicon demonstrator has then been fabricated in a 65nm technology in order to fully demonstrate the methodology. The fabricated dataset of circuits is extracted from typical and corner wafers. This feature is very important since corner circuits are the worst design cases and therefore the most difficult to calibrate. In our case, corner circuits represent more than the two third of the overall dataset and the calibration can still be proven. In details, fabrication yield based on 3 sigma performance specifications is increased from 21% to 93%. This is a major performance of the technique, knowing that worst case circuits are very rare in industrial fabrication.La demande courante de connectivité instantanée impose un cahier des charges très strict sur la fabrication des circuits Radio-Fréquences (RF). Les circuits doivent donc être transférées vers les technologies les plus avancées, initialement introduites pour augmenter les performances des circuits purement numériques. De plus, les circuits RF sont soumis à de plus en plus de variations et cette sensibilité s’accroît avec l’avancées des technologies. Ces variations sont par exemple les variations du procédé de fabrication, la température, l’environnement, le vieillissement… Par conséquent, la méthode classique de conception de circuits “pire-cas” conduit à une utilisation non-optimale du circuit dans la vaste majorité des conditions, en termes de performances et/ou de consommation. Ces variations doivent donc être compensées, en utilisant des techniques d’adaptation.De manière plus importante encore, le procédé de fabrication des circuits introduit de plus en plus de variabilité dans les performances des circuits, ce qui a un impact important sur le rendement de fabrication des circuits. Pour cette raison, les circuits RF sont difficilement fabriqués dans les technologies CMOS les plus avancées comme les nœuds 32nm ou 22nm. Dans ce contexte, les performances des circuits RF doivent êtres calibrées après fabrication pour prendre en compte ces variations et retrouver un haut rendement de fabrication.Ce travail de these présente une méthode de calibration post-fabrication pour les circuits RF. Cette méthodologie est appliquée pendant le test de production en ajoutant un minimum de coût, ce qui est un point essentiel car le coût du test est aujourd’hui déjà comparable au coût de fabrication d’un circuit RF et ne peut être augmenté d’avantage. Par ailleurs, la puissance consommée est aussi prise en compte pour que l’impact de la calibration sur la consommation soit minimisé. La calibration est rendue possible en équipant le circuit avec des nœuds de réglages et des capteurs. L’identification de la valeur de réglage optimale du circuit est obtenue en un seul coup, en testant les performances RF une seule et unique fois. Cela est possible grâce à l’utilisation de capteurs de variations du procédé de fabrication qui sont invariants par rapport aux changements des nœuds de réglage. Un autre benefice de l’utilisation de ces capteurs de variation sont non-intrusifs et donc totalement transparents pour le circuit sous test. La technique de calibration a été démontrée sur un amplificateur de puissance RF utilisé comme cas d’étude. Une première preuve de concept est développée en utilisant des résultats de simulation.Un démonstrateur en silicium a ensuite été fabriqué en technologie 65nm pour entièrement démontrer le concept de calibration. L’ensemble des puces fabriquées a été extrait de trois types de wafer différents, avec des transistors aux performances lentes, typiques et rapides. Cette caractéristique est très importante car elle nous permet de considérer des cas de procédé de fabrication extrêmes qui sont les plus difficiles à calibrer. Dans notre cas, ces circuits représentent plus des deux tiers des puces à disposition et nous pouvons quand même prouver notre concept de calibration. Dans le détails, le rendement de fabrication passe de 21% avant calibration à plus de 93% après avoir appliqué notre méthodologie. Cela constitue une performance majeure de notre méthodologie car les circuits extrêmes sont très rares dans une fabrication industrielle

Doctor of Philosophy

dissertationSince the late 1950s, scientists have been working toward realizing implantable devices that would directly monitor or even control the human body's internal activities. Sophisticated microsystems are used to improve our understanding of internal biological processes in animals and humans. The diversity of biomedical research dictates that microsystems must be developed and customized specifically for each new application. For advanced long-term experiments, a custom designed system-on-chip (SoC) is usually necessary to meet desired specifications. Custom SoCs, however, are often prohibitively expensive, preventing many new ideas from being explored. In this work, we have identified a set of sensors that are frequently used in biomedical research and developed a single-chip integrated microsystem that offers the most commonly used sensor interfaces, high computational power, and which requires minimum external components to operate. Included peripherals can also drive chemical reactions by setting the appropriate voltages or currents across electrodes. The SoC is highly modular and well suited for prototyping in and ex vivo experimental devices. The system runs from a primary or secondary battery that can be recharged via two inductively coupled coils. The SoC includes a 16-bit microprocessor with 32 kB of on chip SRAM. The digital core consumes 350 μW at 10 MHz and is capable of running at frequencies up to 200 MHz. The integrated microsystem has been fabricated in a 65 nm CMOS technology and the silicon has been fully tested. Integrated peripherals include two sigma-delta analog-to-digital converters, two 10-bit digital-to-analog converters, and a sleep mode timer. The system also includes a wireless ultra-wideband (UWB) transmitter. The fullydigital transmitter implementation occupies 68 x 68 μm2 of silicon area, consumes 0.72 μW static power, and achieves an energy efficiency of 19 pJ/pulse at 200 MHz pulse repetition frequency. An investigation of the suitability of the UWB technology for neural recording systems is also presented. Experimental data capturing the UWB signal transmission through an animal head are presented and a statistical model for large-scale signal fading is developed

Novel Predistortion System for 4G/5G Small-Cell and Wideband Transmitters

To meet the growing demand for mobile data, various technologies are being introduced to wireless networks to increase system capacity. On one hand, large number of small-cell base stations are adopted to serve the reduced cell size; on the other hand, millimeter wave (mm-wave) systems with large antenna arrays that transmit ultra-wideband signals are expected in fifth generation (5G) networks. Power amplifiers (PAs), responsible for boosting the radio frequency (RF) signal power, are the most critical components in base station transmitters, and dominate the overall efficiency and linearity of the system. The design challenges to balance the contradictory requirements of efficiency and linearity of the PAs are usually addressed by linearization techniques, particularly the digital predistortion (DPD) system. However, existing DPD solutions face increasing difficulties keeping up with new developments in base station technologies. When considering sub-6 GHz small-cell base station transmitters, analog and RF predistortion techniques have recently received renewed attention due to their inherent low power nature. Their achievable linearization capacity is significantly limited, however, largely by their implementation complexity in realizing the needed predistortion models in analog circuitry. On the other hand, despite significant developments in DPD models for wideband signals, the implementations of such DPD models in practical hardware have received relatively little attention. Yet the conventional implementation of a DPD engine is limited by the maximum clock frequency of the digital circuitry employed and cannot be scaled to satisfy the growing bandwidth of transmitted signals for 5G networks. Furthermore, both analog and digital solutions require a transmitter-observation-receiver (TOR) to capture the PA outputs, necessitates the use of analog-to-digital converters (ADCs) whose complexity and power consumption increase with signal bandwidth. Such trend is not scalable for future base stations, and new innovations in feedback and training methods are required. This thesis presents a number of contributions to address the above identified challenges. To reduce the power overhead of the linearization system, a digitally-assisted analog-RF predistortion (DA-ARFPD) system that uses a novel predistortion model is introduced. The proposed finite-impulse-response assisted envelope memory polynomial (FIR-EMP) model allows for a reduction of hardware implementation complexity while maintaining good linearization capacity and low power overhead. A two-step small-signal-assisted parameter identification (SSAPI) algorithm is devised to estimate the parameters of the two main blocks of the FIR-EMP model, such that the training can be completed efficiently. A DA-ARFPD test bench has been built, which incorporates major RF components, to assess the validity of the proposed FIR-EMP scheme and the SSAPI algorithm. Measurement results show that the proposed FIR-EMP model with SSAPI algorithm can successfully linearize multiple PAs driven with various wideband and carrier-aggregated signals of up to 80~MHz modulation bandwidths for sub-6 GHz systems. Next, a hardware-efficient real-time DPD system with scalable linearization bandwidth for ultra-wideband 5G mm-wave transmitters is proposed. It uses a novel parallel-processing DPD engine architecture to process multiple samples per clock cycle, overcomes the linearization bandwidth limit imposed by the maximum clock rate of digital circuits used in conventional DPD implementation. Potentially unlimited linearization bandwidth could be achieved by using the proposed system with current digital circuit technologies. The linearization performance and bandwidth scalability of the proposed system is demonstrated experimentally using a silicon-based Doherty (DPA) with 400 MHz wideband signal operating at 28 GHz, and over-the-air measurements using a 64-element beamforming array with 800 MHz wideband signal, also at 28 GHz. The proposed DPD system achieves over 2.4 GHz linearization bandwidth using only a 300 MHz core clock for the digital circuits. Finally, to reduce the power consumption and cost of the TOR, a new approach to train the predistorter using under-sampled feedback signal is presented. Using aliased samples of the PA's output captured at either baseband or intermedia frequency (IF), the proposed algorithm is able to compute the coefficients of the predistortion engine to linearize the PA using a direct learning architecture. Experimentally, both the baseband and IF schemes achieve linearization performance comparable to a full-rate system. Implemented together with a parallel-processing based DPD engine on a field-programmable gate array (FPGA) based system-on-chip (SOC), the proposed feedback and training solution achieves over 2.4~GHz linearization bandwidth using an ADC operating at a clock rate of 200 MHz. Its performance is demonstrated experimentally by linearizing a silicon DPA with 200 MHz and 400 MHz signals in conductive measurements, and a 64-element beamforming array with 400 MHz and 800 MHz signals in over-the-air testing

High Performance Local Oscillator Design for Next Generation Wireless Communication

Local Oscillator (LO) is an essential building block in modern wireless radios. In modern wireless radios, LO often serves as a reference of the carrier signal to modulate or demod- ulate the outgoing or incoming data. The LO signal should be a clean and stable source, such that the frequency or timing information of the carrier reference can be well-defined. However, as radio architecture evolves, the importance of LO path design has become much more important than before. Of late, many radio architecture innovations have exploited sophisticated LO generation schemes to meet the ever-increasing demands of wireless radio performances. The focus of this thesis is to address challenges in the LO path design for next-generation high performance wireless radios. These challenges include (1) Congested spectrum at low radio frequency (RF) below 5GHz (2) Continuing miniaturization of integrated wireless radio, and (3) Fiber-fast (>10Gb/s) mm-wave wireless communication. The thesis begins with a brief introduction of the aforementioned challenges followed by a discussion of the opportunities projected to overcome these challenges. To address the challenge of congested spectrum at frequency below 5GHz, novel ra- dio architectures such as cognitive radio, software-defined radio, and full-duplex radio have drawn significant research interest. Cognitive radio is a radio architecture that opportunisti- cally utilize the unused spectrum in an environment to maximize spectrum usage efficiency. Energy-efficient spectrum sensing is the key to implementing cognitive radio. To enable energy-efficient spectrum sensing, a fast-hopping frequency synthesizer is an essential build- ing block to swiftly sweep the carrier frequency of the radio across the available spectrum. Chapter 2 of this thesis further highlights the challenges and trade-offs of the current LO gen- eration scheme for possible use in sweeping LO-based spectrum analysis. It follows by intro- duction of the proposed fast-hopping LO architecture, its implementation and measurement results of the validated prototype. Chapter 3 proposes an embedded phase-shifting LO-path design for wideband RF self-interference cancellation for full-duplex radio. It demonstrates a synergistic design between the LO path and signal to perform self-interference cancellation. To address the challenge of continuing miniaturization of integrated wireless radio, ring oscillator-based frequency synthesizer is an attractive candidate due to its compactness. Chapter 4 discussed the difficulty associated with implementing a Phase-Locked Loop (PLL) with ultra-small form-factor. It further proposes the concept sub-sampling PLL with time- based loop filter to address these challenges. A 65nm CMOS prototype and its measurement result are presented for validation of the concept. In shifting from RF to mm-wave frequencies, the performance of wireless communication links is boosted by significant bandwidth and data-rate expansion. However, the demand for data-rate improvement is out-pacing the innovation of radio architectures. A >10Gb/s mm-wave wireless communication at 60GHz is required by emerging applications such as virtual-reality (VR) headsets, inter-rack data transmission at data center, and Ultra-High- Definition (UHD) TV home entertainment systems. Channel-bonding is considered to be a promising technique for achieving >10Gb/s wireless communication at 60GHz. Chapter 5 discusses the fundamental radio implementation challenges associated with channel-bonding for 60GHz wireless communication and the pros and cons of prior arts that attempted to address these challenges. It is followed by a discussion of the proposed 60GHz channel- bonding receiver, which utilizes only a single PLL and enables both contiguous and non- contiguous channel-bonding schemes. Finally, Chapter 6 presents the conclusion of this thesis