In this work, a 3.5 GHz RF Transmitter and Successive Approximation ADC design has been presented. The transmitter serves as an intermediate block which translates 350 MHz signal into 3.5 GHz signal. This signal is applied to 6-40 GHz wideband transmitter. The emphasis is on the design of Up conversion Mixer with high linearity, low noise and moderate image rejection performance. The successive approximation analog to digital converter was designed as a part of feedback loop control, which consists of a sensor circuit to detect the temperature changes in a power amplifier and the ADC to convert the sensor output to digital data. The data is used to determine the necessary control signals to restore the performance of the power amplifier. The circuits have been designed and implemented in ST Microelectronics CMOS 90nm process.

Charge-scaling (CS) successive approximation register (SAR) ADC's are widely used in the design of low power electronics. Significant portions of CS-SAR ADC power are consumed by CS capacitor arrays and comparator circuits. This Dissertation presents circuit techniques to reduce the power consumption of both CS capacitor array and the latch comparator during ADC operations. The impacts of the proposed techniques on ADC accuracies are analyzed and circuit techniques are presented to address the accuracy concerns. The dissertation also presents techniques to cope with capacitor mismatches, which becomes more significant with the use of very small unit capacitors in the CS array. These techniques rely on a novel programmable CS capacitor array that allow optimally grouping the unit capacitors. Based on a 0.13um CMOS technology the proposed techniques are verified with extensive circuit simulation. Post layout simulations are done to evaluate the proposed techniques for energy efficient CS capacitor array.

This research investigates lower-power lower-voltage analog circuit techniques suitable for wireless sensor applications. Wireless sensors have been used in a wide range of applications and will become ubiquitous with the revolution of internet of things (IoT). Due to the demand of low cost, miniature desirable size and long operating cycle, passive wireless sensors which don't require battery are more preferred. Such sensors harvest energy from energy sources in the environment such as radio frequency (RF) waves, vibration, thermal sources, etc. As a result, the obtained energy is very limited. This creates strong demand for low power, lower voltage circuits. The RF and analog circuits in the wireless sensor usually consume most of the power. This motivates the research presented in the dissertation. Specially, the research focuses on the design of a low power high efficiency regulator, low power Resistance to Digital Converter (RDC), low power Successive Approximation Register (SAR) Analog to Digital Converter (ADC) with parasitic error reduction and a low power low voltage Low Dropout (LDO) regulator. This dissertation includes a low power analog circuit design for the RFID wireless sensor which consists of the energy harvest circuits (an optimized rectifier and a regulator with high current efficiency) and a sensor measurement circuit (RDC), a single end sampling SAR ADC with no error induced by the parasitic capacitance and a digital loop LDO whose line and load variation response is improved. These techniques will boost the design of the wireless sensor and they can also be used in other similar low power design.

The key requirements of a reliable neural signal recording system include low power to support long-term monitoring, low noise, minimum tissue damage, and wireless transmission. The neural spikes are also detected and sorted on-chip/off-chip to implement closed-loop neuromodulation in a high channel count setup. All these features together constitute an empirical neural recording system for neuroscience research. In this prospectus, we propose to develop a neural signal acquisition system with wireless transmission and feature extraction. We start by designing a prototype entirely built with commercial-off-the-shelf components, which includes recording and wireless transmission of synthetic neural data and feature extraction. We then conduct the CMOS implementation of the low-power multi-channel neural signal recording read-out circuit, which enables the in-vivo recording with a small form factor. Another direction of this thesis is to design a self-powered motion tracking read-out circuit for wearable sensors. As the wearable industry continues to advance, the need for self-powered medical devices is growing significantly. In this line of research, we propose a self-powered motion sensor based on reverse electrowetting-on-dielectric (REWOD) with low-power integrated electronics for remotely monitoring health conditions. We design the low-power read-out circuit for a wide range of input charges, which is generated from the REWOD sensor.

Human brain and related topics like neuron spikes and their active potentials have become more and more attractive to people these days, as these issues are extremely helpful for curing many neural injuries and cognitive diseases. One method to discover this field is by designing a chip embedded in brains with probes to actual neurons. It is obvious that batteries are not practical for these applications and thereby RF radiation is used as power sources, revealing that chips should operate under a very low power supply. Since neural signals are analog waveforms, analog-to-digital converter (A/D converter, ADC) is the key component in a neural recorder chip. This thesis proposes the complete design of a low power 8-bit successive approximation register (SAR) A/D converter for use in a wireless neural recorder chip, realizing the function of digitizing a sampled neural signal with a frequency distribution of 10Hz to 10kHz. A modified energy-saving capacitor array in the SAR structure is provided to help save power dissipation. Therefore, the ADC shall operate within a power budget of 20­μW maximum from a 1­V power source, at a clock frequency of 500kHz corresponding to a conversion rate of 55.5-kS/s. All the circuits are designed and implemented based on the IBM/Global Foundries 8HP 130nm BiCMOS technology. Simulations of schematic and layout versions are done respectively to verify the functionality, linearity and power consumption of the ADC. Key words: Successive approximation register analog-to-digital converter (SAR-ADC), low power design, energy-saving capacitor array, neural recorder applications

Power consumption is one of the main design constraints in today’s integrated circuits. For systems powered by small non-rechargeable batteries over their entire lifetime, such as medical implant devices, ultra-low power consumption is paramount. In these systems, analog-to-digital converters (ADCs) are key components as the interface between the analog world and the digital domain. This thesis addresses the design challenges, strategies, as well as circuit techniques of ultra-low-power ADCs for medical implant devices. Medical implant devices, such as pacemakers and cardiac defibrillators, typically requirelow-speed, medium-resolution ADCs. The successive approximation register (SAR) ADC exhibits significantly high energy efficiency compared to other prevalent ADC architectures due to its good tradeoffs among power consumption, conversion accuracy, and design complexity. To design an energy-efficient SAR ADC, an understanding of its error sources as well as its power consumption bounds is essential. This thesis analyzes the power consumption bounds of SAR ADC: 1) at low resolution, the power consumption is bounded by digital switching power; 2) at medium-to-high resolution, the power consumption is bounded by thermal noise if digital assisted techniques are used to alleviate mismatch issues; otherwise it is bounded by capacitor mismatch.  Conversion of the low frequency bioelectric signals does not require high speed, but ultra-low-power operation. This combined with the required conversion accuracy makes the design of such ADCs a major challenge. It is not straightforward to effectively reduce the unnecessary speed for lower power consumption using inherently fast components in advanced CMOS technologies. Moreover, the leakage current degrades the sampling accuracy during the long conversion time, and the leakage power consumption contributes to a significant portion of the total power consumption. Two SAR ADCs have been implemented in this thesis. The first ADC, implemented in a 0.13-µm CMOS process, achieves 9.1 ENOB with 53-nW power consumption at 1 kS/s. The second ADC, implemented in a 65-nm CMOS process, achieves the same resolution at 1 kS/s with a substantial (94%) improvement in power consumption, resulting in 3-nW total power consumption. Our work demonstrates that the ultra-low-power operation necessitates maximum simplicity in the ADC architecture.

Die vorliegende Arbeit behandelt den Entwurf eines ADCs nach dem sukzessiven Approximationsverfahren (SAR). Ausgehend von den Systemanforderungen erfolgt eine Ableitung der Spezifikation des zu entwerfenden ADCs. Theoretische Betrachtungen und Highlevelsimulationen in Matlab wählen die optimale Architektur der Einzelkomponenten - kapazitives DAC Array, Komparator, Ablaufsteuerung - aus. Die Implementation selbst findet für die Analogschaltungsteile auf Transistorebene und für die digitalen Komponenten auf RT-Ebene in VHDL statt. Sie bilden die Grundlage für die Realisierung des Layouts. In dem Zusammenhang stellt die Arbeit die gängigsten Matchingmethoden für elektronische Bauelemente vor. Abschließende PEX-Simulationen (parasitic Extraction) ermitteln die statischen (INL/DNL) wie dynamischen Kennwerte (SNR) des SAR-ADCs.:Abkürzungsverzeichnis iii Formelzeichen v 1 Einleitung 1 2 Grundlagen 2 2.1 Analog/Digital-Umsetzer 2 2.1.1 Umsetzungsverfahren 2 2.1.2 Statische Kennwerte 8 2.1.3 Dynamische Kennwerte 12 2.2 Technologie 17 2.2.1 Übersicht 17 2.2.2 MOS-Transistoren 17 2.2.3 Kapazitäten 18 2.2.4 Widerstände 18 2.3 Hardwarebeschreibungssprache 19 2.3.1 Übersicht 19 2.3.2 Zustandsautomat 19 2.3.3 Look-Ahead-Ausgang 20 3 Spezifikation 21 4 ADU-Topologie 23 4.1 Vorüberlegungen 23 4.1.1 Umsetzungsverfahren 23 4.1.2 Vergleich Widerstand/Kapazität 23 4.1.3 Differenziell Vs. Single-Ended 24 4.1.4 Kapazitätsarray 25 4.2 ADC High-Level Modell 30 4.2.1 Funktionsblöcke 30 4.2.2 Matlab/Simulink 31 4.2.3 Simulation 34 4.3 Parasitäre Effekte 37 4.3.1 Substratkapazität 37 4.3.2 Komparatoroffset 39 5 Schaltungsdesign & -simulation 41 5.1 Komparator 41 5.1.1 Spezifikation 41 5.1.2 Latch 41 5.1.3 Vorverstärker 43 5.1.4 Gesamtsystem 46 5.2 Schalter 46 5.2.1 Funktionsweise 46 5.2.2 Ladungseintrag 46 5.2.3 Dimensionierung & Simulation 47 5.3 Kapazitätsarray 51 5.4 SAR-Controller 51 5.4.1 Vorüberlegung 51 5.4.2 RTL Design 52 5.4.3 Simulation 55 5.4.4 Synthese 57 5.4.5 Optimierung 59 5.5 ADC (Toplevel) 59 5.5.1 Architektur 59 5.5.2 Simulation 61 6 Layout 64 6.1 Komparator 65 6.1.1 Vorverstärker 1 65 6.1.2 Vorverstärker 2 66 6.1.3 Dynamisches Latch 66 6.2 Transmission Gates 67 6.3 Kapazitätsarray 68 6.4 SAR-Controller 70 6.5 ADC (Toplevel) 70 6.6 PEX Simulation 72 6.6.1 Statischer Test 72 6.6.2 Dynamischer Test 73 7 Zusammenfassung 74 Literaturverzeichnis 76 Bücher 76 Skripte und Schriften 76 Internetlinks 78 Abbildungsverzeichnis 79 Tabellenverzeichnis 82 Anhang 84

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Chronic recording of neural signals is indispensable in designing efficient brain machine interfaces and to elucidate human neurophysiology. The advent of multi-channel micro-electrode arrays has driven the need for electronic store cord neural signals from many neurons. The continuous increase in demand of data from more number of neurons is challenging for the design of an efficient neural recording frontend(NRFE). Power consumption per channel and data rate minimization are two key problems which need to be addressed by next generation of neural recording systems. Area consumption per channel must be low for small implant size. Dynamic range in NRFE can vary with time due to change in electrode-neuron distance or background noise which demands adaptability. In this thesis, techniques to reduce power-per-channel and area-per-channel in a NRFE, via new circuits and architectures, are proposed. An area efficient low power neural LNA is presented in UMC 0.13 μm 1P8M CMOS technology. The amplifier can be biased adaptively from 200 nA to 2 μA , modulating input referred noise from 9.92 μV to 3.9μV . We also describe a low noise design technique which minimizes the noise contribution of the load circuitry. Optimum sizing of the input transistors minimizes the accentuation of the input referred noise of the amplifier. It obviates the need of large input coupling capacitance in the amplifier which saves considerable amount of chip area. In vitro experiments were performed to validate the applicability of the neural LNA in neural recording systems. ADC is another important block in a NRFE. An 8-bit SAR ADC along with the input and reference buffer is implemented in 0.13 μm CMOS technology. The use of ping-pong input sampling is emphasized for multichannel input to alleviate the bandwidth requirement of the input buffer. To reduce the output data rate, the A/D process is only enabled through a proposed activity dependent A/D scheme which ensures that the background noise is not processed. Based on the dynamic range requirement, the ADC resolution is adjusted from 8 to 1 bit at 1 bit step to reduce power consumption linearly. The ADC consumes 8.8 μW from1Vsupply at1MS/s and achieves ENOB of 7.7 bit. The ADC achieves FoM of 42.3 fJ/conversion in 0.13 μm CMOS technology. Power consumption in SARADCs is greatly benefited by CMOS scaling due to its highly digital nature. However the power consumption in the capacitive DAC does not scale as well as the digital logic. In this thesis, two energy-efficient DAC switching techniques, Flip DAC and Quaternary capacitor switching, are proposed to reduce their energy consumption. Using these techniques, the energy consumption in the DAC can be reduced by 37 % and 42.5 % compared to the present state-of-the-art. A novel concept of code-independent energy consumption is introduced and emphasized. It mitigates energy consumption degradation with small input signal dynamic range.

Silicon carbide (SiC) integrated circuits (ICs) can enable the emergence of robust and reliable systems, including data acquisition and on-site control for extreme environments with high temperature and high radiation such as deep earth drilling, space and aviation, electric and hybrid vehicles, and combustion engines. In particular, SiC ICs provide significant benefit by reducing power dissipation and leakage current at temperatures above 300 °C compared to the Si counterpart. In fact, Si-based ICs have a limited maximum operating temperature which is around 300 °C for silicon on insulator (SOI). Owing to its superior material properties such as wide bandgap, three times larger than Silicon, and low intrinsic carrier concentration, SiC is an excellent candidate for high-temperature applications. In this thesis, analog and mixed-signal circuits have been implemented using SiC bipolar technology, including bandgap references, amplifiers, a master-slave comparator, an 8-bit R-2R ladder-based digital-to-analog converter (DAC), a 4-bit flash analog-to-digital converter (ADC), and a 10-bit successive-approximation-register (SAR) ADC. Spice models were developed at binned temperature points from room temperature to 500 °C, to simulate and predict the circuits’ behavior with temperature variation. The high-temperature performance of the fabricated chips has been investigated and verified over a wide temperature range from 25 °C to 500 °C. A stable gain of 39 dB was measured in the temperature range from 25 °C up to 500 °C for the inverting operational amplifier with ideal closed-loop gain of 40 dB. Although the circuit design in an immature SiC bipolar technology is challenging due to the low current gain of the transistors and lack of complete AC models, various circuit techniques have been applied to mitigate these problems. This thesis details the challenges faced and methods employed for device modeling, integrated circuit design, layout implementation and finally performance verification using on-wafer characterization of the fabricated SiC ICs over a wide temperature range. / <p>QC 20170905</p>