Implementation of a 200 MSps 12-bit SAR ADC

Analog-to-digital converters (ADCs) with high conversion frequency, often based on pipelined architectures, are used for measuring instruments, wireless communication and video applications. Successive approximation register (SAR) converters offer a compact and power efficient alternative but the conversion speed is typically designed for lower frequencies. In this thesis a low-power 12-bit 200 MSps SAR ADC based on charge redistribution was designed for a 28 nm CMOS technology. The proposed design uses an efficient SAR algorithm (merged capacitor switching procedure) to reduce power consumption due to capacitor charging by 88 % compared to a conventional design, as well as reducing the total capacitor area by half. Sampling switches were bootstrapped for increased linearity compared to simple transmission gates. Another feature of the low power design is a fully-dynamic comparator which does not require a preamplifier. Pre-layout simulations of the SAR ADC with 800 MHz input frequency shows an SNDR of 64.8 dB, corresponding to an ENOB of 10.5, and an SFDR of 75.3 dB. The total power consumption is 1.77 mW with an estimated value of 500 W for the unimplemented digital logic. Calculation of the Schreier figure-of-merit was done with an input signal at the Nyquist frequency. The simulated SNDR, SFDR and power equals 69.5 dB, 77.3 dB and 1.9 mW respectively, corresponding to a figure-of merit of 176.6 dB.Från analogt till digitalt - snabba och strömsnåla omvandlare Dagens digitala samhälle ställer höga krav på prestanda och effektivitet. I samarbete med Ericsson i Lund har en krets för signalomvandling utvecklats. Genom smart design uppnås hög hastighet och låg strömförbrukning som ligger i forskningens framkant. Från analogt till digitalt Ett viktigt byggblock för telekommunikation och videoapplikationer är så kallade A/D-omvandlare, som översätter mellan analoga signaler (till exempel ljud) och digitala signaler bestående av ettor och nollor. En väldigt effektiv metod för A/D-omvandling bygger på så kallad successiv approximation. Metoden innebär att signalen som ska omvandlas jämförs med en referensnivå, som stegvis justeras för att närma sig signalens värde. Till slut har man en tillräckligt god uppskattning av värdet som ska mätas. Just en sådan omvandlare har utvecklats med höga krav på hastighet och energiförbrukning. Detta gjordes genom datorsimuleringar av modeller som beskriver kretsen. Referensnivån skapas ofta genom att styra ett nätverk som lagrar elektrisk laddning. Omvandlingens noggrannhet, eller upplösning, beror på hur många nivåer som finns tillgängliga det vill säga hur nära signalens värde man kan komma. I den designade kretsen finns hela 4096 nivåer! Det finns många källor till osäkerhet i systemet, bland annat hur exakta referensnivåerna är och hur bra jämförelsen med insignalen kan göras. Eftersom dessa eventuellt kan leda till en försämring av omvandlingens noggrannhet måste alla delar i kretsen utformas med detta i åtanke. Höga hastigheter Eftersom det krävs många steg för referensnivån att närma sig signalens värde är den maximala omvandlingshastigheten ofta begränsad. Med teknikens utveckling öppnas nya möjligheter i takt med att mikrochippens enskilda komponenter blir snabbare. Modern forskning visar att omvandlare baserade på successiv approximation kan uppnå hastigheter på flera miljoner mätvärden varje sekund, vilket även den utvecklade kretsen klarar av. Effektiv design Nya metoder för successiv approximation möjliggör stora besparingar när det gäller effektförbrukning, till exempel genom att effektivisera upp- och urladdningen av nätverket. Genom små ändringar kunde nätverkets energiförbrukning minskas med över 90 % samtidigt som dess area halverades. Eftersom produktionskostnaden för integrerade kretsar är hög medför varje minskning av kretsens area att kostnaden sjunker

A neural probe with up to 966 electrodes and up to 384 configurable channels in 0.13 μm SOI CMOS

In vivo recording of neural action-potential and local-field-potential signals requires the use of high-resolution penetrating probes. Several international initiatives to better understand the brain are driving technology efforts towards maximizing the number of recording sites while minimizing the neural probe dimensions. We designed and fabricated (0.13-μm SOI Al CMOS) a 384-channel configurable neural probe for large-scale in vivo recording of neural signals. Up to 966 selectable active electrodes were integrated along an implantable shank (70 μm wide, 10 mm long, 20 μm thick), achieving a crosstalk of −64.4 dB. The probe base (5 × 9 mm2) implements dual-band recording and a 1

Silicon-on-Insulator Power Management Integrated Circuit for Thin-Film Solid-State Lithium-Ion Micro-Batteries

This thesis presents the design and implementation of a power management integrated circuit (IC) that is capable of both current and voltage charging thin-film, solid-state, lithium-ion micro-batteries. The power management system has been fabricated using a single-poly, 0.35-ìm, partially-depleted, silicon-on-insulator process (PD-SOI). The system contains a temperature stable current charger (current generator and a 4-bit current-mode DAC), a regulated voltage supply (voltage amplifier), and a voltage monitoring circuit (2-bit flash ADC). Experimental results of the first version of the power management system show proper functionality was obtained. The current charger produced a 2% worst-case variation in output current over the temperature range 0–100°C. The regulated voltage output was measured to be 4.4 V and the digital outputs of the flash ADC transitioned at 3.45 and 4.76 V

CMOS Data Converters for Closed-Loop mmWave Transmitters

With the increased amount of data consumed in mobile communication systems, new solutions for the infrastructure are needed. Massive multiple input multiple output (MIMO) is seen as a key enabler for providing this increased capacity. With the use of a large number of transmitters, the cost of each transmitter must be low. Closed-loop transmitters, featuring high-speed data converters is a promising option for achieving this reduced unit cost.In this thesis, both digital-to-analog (D/A) and analog-to-digital (A/D) converters suitable for wideband operation in millimeter wave (mmWave) massive MIMO transmitters are demonstrated. A 2 76 bit radio frequency digital-to-analog converter (RF-DAC)-based in-phase quadrature (IQ) modulator is demonstrated as a compact building block, that to a large extent realizes the transmit path in a closed-loop mmWave transmitter. The evaluation of an successive-approximation register (SAR) analog-to-digital converter (ADC) is also presented in this thesis. Methods for connecting simulated and measured performance has been studied in order to achieve a better understanding about the alternating comparator topology.These contributions show great potential for enabling closed-loop mmWave transmitters for massive MIMO transmitter realizations

Data Conversion Within Energy Constrained Environments

Within scientific research, engineering, and consumer electronics, there is a multitude of new discrete sensor-interfaced devices. Maintaining high accuracy in signal quantization while staying within the strict power-budget of these devices is a very challenging problem. Traditional paths to solving this problem include researching more energy-efficient digital topologies as well as digital scaling.;This work offers an alternative path to lower-energy expenditure in the quantization stage --- content-dependent sampling of a signal. Instead of sampling at a constant rate, this work explores techniques which allow sampling based upon features of the signal itself through the use of application-dependent analog processing. This work presents an asynchronous sampling paradigm, based off the use of floating-gate-enabled analog circuitry. The basis of this work is developed through the mathematical models necessary for asynchronous sampling, as well the SPICE-compatible models necessary for simulating floating-gate enabled analog circuitry. These base techniques and circuitry are then extended to systems and applications utilizing novel analog-to-digital converter topologies capable of leveraging the non-constant sampling rates for significant sample and power savings

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm² × fJ/conv-step Efficiency and 0.97 NEF

This letter presents an energy-and-area-efficient ac-coupled front-end for the multichannel recording of wideband neural signals. The proposed unit conditions local field and action potentials using an inverter-based capacitively coupled low-noise amplifier, followed by a per-channel 10-b asynchronous SAR ADC. The adaptation of unit-length capacitors minimizes the ADC area and relaxes the amplifier gain so that small coupling capacitors can be integrated. The prototype in 65-nm CMOS achieves 4× smaller area and 3× higher energy–area efficiency compared to the state of the art with 164 μm×40μm footprint and 0.78 mm²× fJ/conv-step energy-area figure of merit. The measured 0.65- μW power consumption and 3.1 - μVrms input-referred noise within 1 Hz–10 kHz bandwidth correspond to a noise efficiency factor of 0.97

An AC-Coupled Wideband Neural Recording Front-End With Sub-1 mm² × fJ/conv-step Efficiency and 0.97 NEF

This letter presents an energy-and-area-efficient ac-coupled front-end for the multichannel recording of wideband neural signals. The proposed unit conditions local field and action potentials using an inverter-based capacitively coupled low-noise amplifier, followed by a per-channel 10-b asynchronous SAR ADC. The adaptation of unit-length capacitors minimizes the ADC area and relaxes the amplifier gain so that small coupling capacitors can be integrated. The prototype in 65-nm CMOS achieves 4× smaller area and 3× higher energy–area efficiency compared to the state of the art with 164 μm×40μm footprint and 0.78 mm²× fJ/conv-step energy-area figure of merit. The measured 0.65- μW power consumption and 3.1 - μVrms input-referred noise within 1 Hz–10 kHz bandwidth correspond to a noise efficiency factor of 0.97

High Temperature Silicon Carbide Mixed-signal Circuits for Integrated Control and Data Acquisition

Wide bandgap semiconductor materials such as gallium nitride (GaN) and silicon carbide have grown in popularity as a substrate for power devices for high temperature and high voltage applications over the last two decades. Recent research has been focused on the design of integrated circuits for protection and control in these wide bandgap materials. The ICs developed in SiC and GaN can not only complement the power devices in high voltage and high frequency applications, but can also be used for standalone high temperature control and data acquisition circuitry. This dissertation work aims to explore the possibilities in high temperature and wide bandgap circuit design by developing a host of mixed-signal circuits that can be used for control and data acquisition. These include a family of current-mode signal processing circuits, general purpose amplifiers and comparators, and 8-bit data converters. The signal processing circuits along with amplifiers and comparators are then used to develop an integrated mixed-signal controller for a DC-DC flyback converter in a microinverter application. The 8-bit SAR ADC and the 8-bit R-2R ladder DAC open up the possibility of a remote data acquisition and control system in high temperature environments. The circuits and systems presented here offer a gateway to great opportunities in high temperature and power electronics ICs in SiC

Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions

Massive MIMO is a compelling wireless access concept that relies on the use of an excess number of base-station antennas, relative to the number of active terminals. This technology is a main component of 5G New Radio (NR) and addresses all important requirements of future wireless standards: a great capacity increase, the support of many simultaneous users, and improvement in energy efficiency. Massive MIMO requires the simultaneous processing of signals from many antenna chains, and computational operations on large matrices. The complexity of the digital processing has been viewed as a fundamental obstacle to the feasibility of Massive MIMO in the past. Recent advances on system-algorithm-hardware co-design have led to extremely energy-efficient implementations. These exploit opportunities in deeply-scaled silicon technologies and perform partly distributed processing to cope with the bottlenecks encountered in the interconnection of many signals. For example, prototype ASIC implementations have demonstrated zero-forcing precoding in real time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing of 8 terminals). Coarse and even error-prone digital processing in the antenna paths permits a reduction of consumption with a factor of 2 to 5. This article summarizes the fundamental technical contributions to efficient digital signal processing for Massive MIMO. The opportunities and constraints on operating on low-complexity RF and analog hardware chains are clarified. It illustrates how terminals can benefit from improved energy efficiency. The status of technology and real-life prototypes discussed. Open challenges and directions for future research are suggested.Comment: submitted to IEEE transactions on signal processin

Deep Trek High Temperature Electronics Project

This report summarizes technical progress achieved during the cooperative research agreement between Honeywell and U.S. Department of Energy to develop high-temperature electronics. Objects of this development included Silicon-on-Insulator (SOI) wafer process development for high temperature, supporting design tools and libraries, and high temperature integrated circuit component development including FPGA, EEPROM, high-resolution A-to-D converter, and a precision amplifier