Design of a low power switched-capacitor pipeline analog-to-digital converter

An Analog to Digital Converter (ADC) is a circuit which converts an analog signal into digital signal. Real world is analog, and the data processed by the computer or by other signal processing systems is digital. Therefore, the need for ADCs is obvious. In this thesis, several novel designs used to improve ADCs operation speed and reduce ADC power consumption are proposed. First, a high speed switched source follower (SSF) sample and hold amplifier without feedthrough penalty is implemented and simulated. The SSF sample and hold amplifier can achieve 6 Bit resolution with sampling rate at 10Gs/s. Second, a novel rail-to-rail time domain comparator used in successive approximation register ADC (SAR ADC) is implemented and simulated. The simulation results show that the proposed SAR ADC can only consume 1.3 muW with a 0.7 V power supply. Finally, a prototype pipeline ADC is implemented and fabricated in an IBM 90nm CMOS process. The proposed design is validated using measurement on a fabricated silicon IC, and the proposed 10-bit ADC achieves a peak signal-to-noise- and-distortion-ratio (SNDR) of 47 dB. This SNDR translates to a figure of merit (FOM) of 2.6N/conversion-step with a 1.2 V power supply

A 90 dB, 85 MHz operational transconductance amplifier (OTA) using gain boosting technique

Gain and speed are the two most important parameters of an amplifier. Optimizing an amplifier for both of these parameters leads to contradicting demands. Various architectures have been reported to obtain high gain from the circuits. Cascode circuits are widely used in circuit design at places where high gain and high output impedances are required. Different architectures like triple cascode topology, dynamic biasing and a positive feedback amplifier have been used to obtain high gains. These architectures have been compared in this thesis along with drawbacks and advantages of each

A Current-Mode Multi-Channel Integrating Analog-to-Digital Converter

Multi-channel analog to digital converters (ADCs) are required where signals from multiple sensors can be digitized. A lower power per channel for such systems is important in order that when the number of channels is increased the power does not increase drastically. Many applications require signals from current output sensors, such as photosensors and photodiodes to be digitized. Applications for these sensors include spectroscopy and imaging. The ability to digitize current signals without converting currents to voltages saves power, area, and the design time required to implement I-to-V converters. This work describes a novel and unique current-mode multi-channel integrating ADC which processes current signals from sensors and converts it to digital format. The ADC facilitates the processing of current analog signals without the use of transconductors. An attempt has been made also to incorporate voltage-mode techniques into the current-mode design so that the advantages of both techniques can be utilized to augment the performance of the system. Additionally since input signals are in the form of currents, the dynamic range of the ADC is less dependant on the supply voltage. A prototype 4-channel ADC design was fabricated in a 0.5-micron bulk CMOS process. The measurement results for a 10Ksps sampling rate include a DNL, which is less than 0.5 LSB, and a power consumption of less than 2mW per channel

Ultra-low power mixed-signal frontend for wearable EEGs

Electronics circuits are ubiquitous in daily life, aided by advancements in the chip design industry, leading to miniaturised solutions for typical day to day problems. One of the critical healthcare areas helped by this advancement in technology is electroencephalography (EEG). EEG is a non-invasive method of tracking a person's brain waves, and a crucial tool in several healthcare contexts, including epilepsy and sleep disorders. Current ambulatory EEG systems still suffer from limitations that affect their usability. Furthermore, many patients admitted to emergency departments (ED) for a neurological disorder like altered mental status or seizures, would remain undiagnosed hours to days after admission, which leads to an elevated rate of death compared to other conditions. Conducting a thorough EEG monitoring in early-stage could prevent further damage to the brain and avoid high mortality. But lack of portability and ease of access results in a long wait time for the prescribed patients. All real signals are analogue in nature, including brainwaves sensed by EEG systems. For converting the EEG signal into digital for further processing, a truly wearable EEG has to have an analogue mixed-signal front-end (AFE). This research aims to define the specifications for building a custom AFE for the EEG recording and use that to review the suitability of the architectures available in the literature. Another critical task is to provide new architectures that can meet the developed specifications for EEG monitoring and can be used in epilepsy diagnosis, sleep monitoring, drowsiness detection and depression study. The thesis starts with a preview on EEG technology and available methods of brainwaves recording. It further expands to design requirements for the AFE, with a discussion about critical issues that need resolving. Three new continuous-time capacitive feedback chopped amplifier designs are proposed. A novel calibration loop for setting the accurate value for a pseudo-resistor, which is a crucial block in the proposed topology, is also discussed. This pseudoresistor calibration loop achieved the resistor variation of under 8.25%. The thesis also presents a new design of a curvature corrected bandgap, as well as a novel DDA based fourth-order Sallen-Key filter. A modified sensor frontend architecture is then proposed, along with a detailed analysis of its implementation. Measurement results of the AFE are finally presented. The AFE consumed a total power of 3.2A (including ADC, amplifier, filter, and current generation circuitry) with the overall integrated input-referred noise of 0.87V-rms in the frequency band of 0.5-50Hz. Measurement results confirmed that only the proposed AFE achieved all defined specifications for the wearable EEG system with the smallest power consumption than state-of-art architectures that meet few but not all specifications. The AFE also achieved a CMRR of 131.62dB, which is higher than any studied architectures.Open Acces

Performance analysis and design optimization of parallel-type slew-rate enhancers for switched-capacitor applications

The design of single-stage OTAs for accurate switched-capacitor circuits involves challenging trade-offs between speed and power consumption. The addition of a Slew-Rate Enhancer (SRE) circuit placed in parallel to the main OTA (parallel-type SRE) constitutes a viable solution to reduce the settling time, at the cost of low-power overhead and no modifications of the main OTA. In this work, a practical analytical model has been developed to predict the settling time reduction achievable with OTA/SRE systems and to show the effect of the various design parameters. The model has been applied to a real case, consisting of the combination of a standard folded-cascode OTA with an existing parallel-type SRE solution. Simulations performed on a circuit designed with a commercial 180-nm CMOS technology revealed that the actual settling-time reduction was significantly smaller than predicted by the model. This discrepancy was explained by taking into account the internal delays of the SRE, which is exacerbated when a high output current gain is combined with high power efficiency. To overcome this problem, we propose a simple modification of the original SRE circuit, consisting in the addition of a single capacitor which temporarily boosts the OTA/SRE currents reducing the internal turn-on delay. With the proposed approach a settling-time reduction of 57% has been demonstrated with an SRE that introduces only a 10% power-overhead with respect of the single OTA solution. The robustness of the results have been validated by means of Monte-Carlo simulations

Digitally Interfaced Analog Correlation Filter System for Object Tracking Applications

Advanced correlation filters have been employed in a wide variety of image processing and pattern recognition applications such as automatic target recognition and biometric recognition. Among those, object recognition and tracking have received more attention recently due to their wide range of applications such as autonomous cars, automated surveillance, human-computer interaction, and vehicle navigation.Although digital signal processing has long been used to realize such computational systems, they consume extensive silicon area and power. In fact, computational tasks that require low to moderate signal-to-noise ratios are more efficiently realized in analog than digital. However, analog signal processing has its own caveats. Mainly, noise and offset accumulation which degrades the accuracy, and lack of a scalable and standard input/output interface capable of managing a large number of analog data.Two digitally-interfaced analog correlation filter systems are proposed. While digital interfacing provided a standard and scalable way of communication with pre- and post-processing blocks without undermining the energy efficiency of the system, the multiply-accumulate operations were performed in analog. Moreover, non-volatile floating-gate memories are utilized as storage for coefficients. The proposed systems incorporate techniques to reduce the effects of analog circuit imperfections.The first system implements a 24x57 Gilbert-multiplier-based correlation filter. The I/O interface is implemented with low-power D/A and A/D converters and a correlated double sampling technique is implemented to reduce offset and lowfrequency noise at the output of analog array. The prototype chip occupies an area of 3.23mm2 and demonstrates a 25.2pJ/MAC energy-efficiency at 11.3 kVec/s and 3.2% RMSE.The second system realizes a 24x41 PWM-based correlation filter. Benefiting from a time-domain approach to multiplication, this system eliminates the need for explicit D/A and A/D converters. Careful utilization of clock and available hardware resources in the digital I/O interface, along with application of power management techniques has significantly reduced the circuit complexity and energy consumption of the system. Additionally, programmable transconductance amplifiers are incorporated at the output of the analog array for offset and gain error calibration. The prototype system occupies an area of 0.98mm2 and is expected to achieve an outstanding energy-efficiency of 3.6pJ/MAC at 319kVec/s with 0.28% RMSE