Matching Items (5)

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Reconfigurable architectures and systems for IoT applications

Description

Internet of Things (IoT) has become a popular topic in industry over the recent years, which describes an ecosystem of internet-connected devices or things that enrich the everyday life by

Internet of Things (IoT) has become a popular topic in industry over the recent years, which describes an ecosystem of internet-connected devices or things that enrich the everyday life by improving our productivity and efficiency. The primary components of the IoT ecosystem are hardware, software and services. While the software and services of IoT system focus on data collection and processing to make decisions, the underlying hardware is responsible for sensing the information, preprocess and transmit it to the servers. Since the IoT ecosystem is still in infancy, there is a great need for rapid prototyping platforms that would help accelerate the hardware design process. However, depending on the target IoT application, different sensors are required to sense the signals such as heart-rate, temperature, pressure, acceleration, etc., and there is a great need for reconfigurable platforms that can prototype different sensor interfacing circuits.

This thesis primarily focuses on two important hardware aspects of an IoT system: (a) an FPAA based reconfigurable sensing front-end system and (b) an FPGA based reconfigurable processing system. To enable reconfiguration capability for any sensor type, Programmable ANalog Device Array (PANDA), a transistor-level analog reconfigurable platform is proposed. CAD tools required for implementation of front-end circuits on the platform are also developed. To demonstrate the capability of the platform on silicon, a small-scale array of 24×25 PANDA cells is fabricated in 65nm technology. Several analog circuit building blocks including amplifiers, bias circuits and filters are prototyped on the platform, which demonstrates the effectiveness of the platform for rapid prototyping IoT sensor interfaces.

IoT systems typically use machine learning algorithms that run on the servers to process the data in order to make decisions. Recently, embedded processors are being used to preprocess the data at the energy-constrained sensor node or at IoT gateway, which saves considerable energy for transmission and bandwidth. Using conventional CPU based systems for implementing the machine learning algorithms is not energy-efficient. Hence an FPGA based hardware accelerator is proposed and an optimization methodology is developed to maximize throughput of any convolutional neural network (CNN) based machine learning algorithm on a resource-constrained FPGA.

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Created

Date Created
  • 2016

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Programmable analog device array (PANDA): transistor-level analog emulation

Description

The design and development of analog/mixed-signal (AMS) integrated circuits (ICs) is becoming increasingly expensive, complex, and lengthy. Rapid prototyping and emulation of analog ICs will be significant in the design

The design and development of analog/mixed-signal (AMS) integrated circuits (ICs) is becoming increasingly expensive, complex, and lengthy. Rapid prototyping and emulation of analog ICs will be significant in the design and testing of complex analog systems. A new approach, Programmable ANalog Device Array (PANDA) that maps any AMS design problem to a transistor-level programmable hardware, is proposed. This approach enables fast system level validation and a reduction in post-Silicon bugs, minimizing design risk and cost. The unique features of the approach include 1) transistor-level programmability that emulates each transistor behavior in an analog design, achieving very fine granularity of reconfiguration; 2) programmable switches that are treated as a design component during analog transistor emulating, and optimized with the reconfiguration matrix; 3) compensation of AC performance degradation through boosting the bias current. Based on these principles, a digitally controlled PANDA platform is designed at 45nm node that can map AMS modules across 22nm to 90nm technology nodes. A systematic emulation approach to map any analog transistor to 45nm PANDA cell is proposed, which achieves transistor level matching accuracy of less than 5% for ID and less than 10% for Rout and Gm. Circuit level analog metrics of a voltage-controlled oscillator (VCO) emulated by PANDA, match to those of the original designs in 22nm and 90nm nodes with less than a 5% error. Several other 90nm and 22nm analog blocks are successfully emulated by the 45nm PANDA platform, including a folded-cascode operational amplifier and a sample-and-hold module (S/H). Further capabilities of PANDA are demonstrated by the first full-chip silicon of PANDA which is implemented on 65nm process This system consists of a 24×25 cell array, reconfigurable interconnect and configuration memory. The voltage and current reference circuits, op amps and a VCO with a phase interpolation circuit are emulated by PANDA.

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Created

Date Created
  • 2013

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Analog fault modeling, simulation and diagnosis

Description

The research objective is fully differential op-amp with common mode feedback, which are applied in filter, band gap, Analog Digital Converter (ADC) and so on as a fundamental component in

The research objective is fully differential op-amp with common mode feedback, which are applied in filter, band gap, Analog Digital Converter (ADC) and so on as a fundamental component in analog circuit. Having modeled various defect and analyzed corresponding probability, defect library could be built after reduced defect simulation.Based on the resolution of microscope scan tool, all these defects are categorized into four groups of defects by both function and location, bias circuit defect, first stage amplifier defect, output stage defect and common mode feedback defect, separately. Each fault result is attributed to one of these four region defects.Therefore, analog testing algorithm and automotive tool could be generated to assist testing engineers to meet the demand of large numbers of chips.

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Created

Date Created
  • 2014

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A CMOS analog front-end circuit for micro-fluxgate sensors

Description

Fluxgate sensors are magnetic field sensors that can measure DC and low frequency AC magnetic fields. They can measure much lower magnetic fields than other magnetic sensors like Hall effect

Fluxgate sensors are magnetic field sensors that can measure DC and low frequency AC magnetic fields. They can measure much lower magnetic fields than other magnetic sensors like Hall effect sensors, magnetoresistive sensors etc. They also have high linearity, high sensitivity and low noise. The major application of fluxgate sensors is in magnetometers for the measurement of earth's magnetic field. Magnetometers are used in navigation systems and electronic compasses. Fluxgate sensors can also be used to measure high DC currents. Integrated micro-fluxgate sensors have been developed in recent years. These sensors have much lower power consumption and area compared to their PCB counterparts. The output voltage of micro-fluxgate sensors is very low which makes the analog front end more complex and results in an increase in power consumption of the system. In this thesis a new analog front-end circuit for micro-fluxgate sensors is developed. This analog front-end circuit uses charge pump based excitation circuit and phase delay based read-out chain. With these two features the power consumption of analog front-end is reduced. The output is digital and it is immune to amplitude noise at the output of the sensor. Digital output is produced without using an ADC. A SPICE model of micro-fluxgate sensor is used to verify the operation of the analog front-end and the simulation results show very good linearity.

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Created

Date Created
  • 2013

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Design of a continuous time sigma delta analog-to-digital converter for operation in extreme environments

Description

In this work, a high resolution analog-to-digital converter (ADC) for use in harsh environments is presented. The ADC is implemented in bulk CMOS technology and is intended for space exploration,

In this work, a high resolution analog-to-digital converter (ADC) for use in harsh environments is presented. The ADC is implemented in bulk CMOS technology and is intended for space exploration, mining and automotive applications with a range of temperature variation in excess of 250°C. A continuous time (CT) sigma delta modulator employing a cascade of integrators with feed forward (CIFF) architecture in a single feedback loop topology is used for implementing the ADC. In order to enable operation in the intended application environments, an RC time constant tuning engine is proposed. The tuning engine is used to maintain linearity of a 10 ksps 20 bit continuous time sigma delta ADC designed for spectroscopy applications in space. The proposed circuit which is based on master slave architecture automatically selects on chip resistors to control RC time constants to an accuracy range of ±5% to ±1%. The tuning range, tuning accuracy and circuit non-idealities are analyzed theoretically. To verify the concept, an experimental chip was fabricated in JAZZ .18µm 1.8V CMOS technology. The tuning engine which occupies an area of .065mm2; consists of only an integrator, a comparator and a shift register. It can achieve a signal to noise and distortion ratio (SNDR) greater than 120dB over a ±40% tuning range.

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Agent

Created

Date Created
  • 2011