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- All Subjects: Electrical Engineering
- All Subjects: engineering
- Genre: Doctoral Dissertation
- Creators: Bliss, Daniel
Description
A dual-channel directional digital hearing aid (DHA) front-end using a fully differential difference amplifier (FDDA) based Microphone interface circuit (MIC) for a capacitive Micro Electro Mechanical Systems (MEMS) microphones and an adaptive-power analog font end (AFE) is presented. The Microphone interface circuit based on FDDA converts the capacitance variations into voltage signal, achieves a noise of 32 dB SPL (sound pressure level) and an SNR of 72 dB, additionally it also performs single to differential conversion allowing for fully differential analog signal chain. The analog front-end consists of 40dB VGA and a power scalable continuous time sigma delta ADC, with 68dB SNR dissipating 67u¬W from a 1.2V supply. The ADC implements a self calibrating feedback DAC, for calibrating the 2nd order non-linearity. The VGA and power scalable ADC is fabricated on 0.25 um CMOS TSMC process. The dual channels of the DHA are precisely matched and achieve about 0.5dB gain mismatch, resulting in greater than 5dB directivity index. This will enable a highly integrated and low power DHA
ContributorsNaqvi, Syed Roomi (Author) / Kiaei, Sayfe (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Chae, Junseok (Committee member) / Barnby, Hugh (Committee member) / Aberle, James T., 1961- (Committee member) / Arizona State University (Publisher)
Created2011
Description
Sensing and controlling current flow is a fundamental requirement for many electronic systems, including power management (DC-DC converters and LDOs), battery chargers, electric vehicles, solenoid positioning, motor control, and power monitoring. Current Shunt Monitor (CSM) systems have various applications for precise current monitoring of those aforementioned applications. CSMs enable current measurement across an external sense resistor (RS) in series to current flow. Two different types of CSMs designed and characterized in this paper. First design used direct current reading method and the other design used indirect current reading method. Proposed CSM systems can sense power supply current ranging from 1mA to 200mA for the direct current reading topology and from 1mA to 500mA for the indirect current reading topology across a typical board Cu-trace resistance of 1 ohm with less than 10 µV input-referred offset, 0.3 µV/°C offset drift and 0.1% accuracy for both topologies. Proposed systems avoid using a costly zero-temperature coefficient (TC) sense resistor that is normally used in typical CSM systems. Instead, both of the designs used existing Cu-trace on the printed circuit board (PCB) in place of the costly resistor. The systems use chopper stabilization at the front-end amplifier signal path to suppress input-referred offset down to less than 10 µV. Switching current-mode (SI) FIR filtering technique is used at the instrumentation amplifier output to filter out the chopping ripple caused by input offset and flicker noise by averaging half of the phase 1 signal and the other half of the phase 2 signal. In addition, residual offset mainly caused by clock feed-through and charge injection of the chopper switches at the chopping frequency and its multiple frequencies notched out by the since response of the SI-FIR filter. A frequency domain Sigma Delta ADC which is used for the indirect current reading type design enables a digital interface to processor applications with minimally added circuitries to build a simple 1st order Sigma Delta ADC. The CSMs are fabricated on a 0.7µm CMOS process with 3 levels of metal, with maximum Vds tolerance of 8V and operates across a common mode range of 0 to 26V for the direct current reading type and of 0 to 30V for the indirect current reading type achieving less than 10nV/sqrtHz of flicker noise at 100 Hz for both approaches. By using a semi-digital SI-FIR filter, residual chopper offset is suppressed down to 0.5mVpp from a baseline of 8mVpp, which is equivalent to 25dB suppression.
ContributorsYeom, Hyunsoo (Author) / Bakkaloglu, Bertan (Thesis advisor) / Kiaei, Sayfe (Committee member) / Ozev, Sule (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2011
Description
Pulse Density Modulation- (PDM-) based class-D amplifiers can reduce non-linearity and tonal content due to carrier signal in Pulse Width Modulation - (PWM-) based amplifiers. However, their low-voltage analog implementations also require a linear- loop filter and a quantizer. A PDM-based class-D audio amplifier using a frequency-domain quantization is presented in this paper. The digital-intensive frequency domain approach achieves high linearity under low-supply regimes. An analog comparator and a single-bit quantizer are replaced with a Current-Controlled Oscillator- (ICO-) based frequency discriminator. By using the ICO as a phase integrator, a third-order noise shaping is achieved using only two analog integrators. A single-loop, singlebit class-D audio amplifier is presented with an H-bridge switching power stage, which is designed and fabricated on a 0.18 um CMOS process, with 6 layers of metal achieving a total harmonic distortion plus noise (THD+N) of 0.065% and a peak power efficiency of 80% while driving a 4-ohms loudspeaker load. The amplifier can deliver the output power of 280 mW.
ContributorsLee, Junghan (Author) / Bakkaloglu, Bertan (Thesis advisor) / Kiaei, Sayfe (Committee member) / Ozev, Sule (Committee member) / Song, Hongjiang (Committee member) / Arizona State University (Publisher)
Created2011
Description
Voltage Control Oscillator (VCO) is one of the most critical blocks in Phase Lock Loops (PLLs). LC-tank VCOs have a superior phase noise performance, however they require bulky passive resonators and often calibration architectures to overcome their limited tuning range. Ring oscillator (RO) based VCOs are attractive for digital technology applications owing to their ease of integration, small die area and scalability in deep submicron processes. However, due to their supply sensitivity and poor phase noise performance, they have limited use in applications demanding low phase noise floor, such as wireless or optical transceivers. Particularly, out-of-band phase noise of RO-based PLLs is dominated by RO performance, which cannot be suppressed by the loop gain, impairing RF receiver's sensitivity or BER of optical clock-data recovery circuits. Wide loop bandwidth PLLs can overcome RO noise penalty, however, they suffer from increased in-band noise due to reference clock, phase-detector and charge-pump. The RO phase noise is determined by the noise coming from active devices, supply, ground and substrate. The authors adopt an auxiliary circuit with inverse delay sensitivity to supply noise, which compensates for the delay variation of inverter cells. Feed-forward noise-cancelling architecture that improves phase noise characteristic of RO based PLLs is presented. The proposed circuit dynamically attenuates RO phase noise contribution outside the PLL bandwidth, or in a preferred band. The implemented noise-cancelling loop potentially enables application of RO based PLL for demanding frequency synthesizers applications, such as optical links or high-speed serial I/Os.
ContributorsMin, Seungkee (Author) / Kiaei, Sayfe (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Ozev, Sule (Committee member) / Towe, Bruce (Committee member) / Arizona State University (Publisher)
Created2011
Description
The medical industry has benefited greatly by electronic integration resulting in the explosive growth of active medical implants. These devices often treat and monitor chronic health conditions and require very minimal power usage. A key part of these medical implants is an ultra-low power two way wireless communication system. This enables both control of the implant as well as relay of information collected. This research has focused on a high performance receiver for medical implant applications. One commonly quoted specification to compare receivers is energy per bit required. This metric is useful, but incomplete in that it ignores Sensitivity level, bit error rate, and immunity to interferers. In this study exploration of receiver architectures and convergence upon a comprehensive solution is done. This analysis is used to design and build a system for validation. The Direct Conversion Receiver architecture implemented for the MICS standard in 0.18 µm CMOS process consumes approximately 2 mW is competitive with published research.
ContributorsStevens, Mark (Author) / Kiaei, Sayfe (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Aberle, James T., 1961- (Committee member) / Barnaby, Hugh (Committee member) / Arizona State University (Publisher)
Created2012
Description
Radio frequency (RF) transceivers require a disproportionately high effort in terms of test development time, test equipment cost, and test time. The relatively high test cost stems from two contributing factors. First, RF transceivers require the measurement of a diverse set of specifications, requiring multiple test set-ups and long test times, which complicates load-board design, debug, and diagnosis. Second, high frequency operation necessitates the use of expensive equipment, resulting in higher per second test time cost compared with mixed-signal or digital circuits. Moreover, in terms of the non-recurring engineering cost, the need to measure complex specfications complicates the test development process and necessitates a long learning process for test engineers. Test time is dominated by changing and settling time for each test set-up. Thus, single set-up test solutions are desirable. Loop-back configuration where the transmitter output is connected to the receiver input are used as the desirable test set- up for RF transceivers, since it eliminates the reliance on expensive instrumentation for RF signal analysis and enables measuring multiple parameters at once. In-phase and Quadrature (IQ) imbalance, non-linearity, DC offset and IQ time skews are some of the most detrimental imperfections in transceiver performance. Measurement of these parameters in the loop-back mode is challenging due to the coupling between the receiver (RX) and transmitter (TX) parameters. Loop-back based solutions are proposed in this work to resolve this issue. A calibration algorithm for a subset of the above mentioned impairments is also presented. Error Vector Magnitude (EVM) is a system-level parameter that is specified for most advanced communication standards. EVM measurement often takes extensive test development efforts, tester resources, and long test times. EVM is analytically related to system impairments, which are typically measured in a production test i environment. Thus, EVM test can be eliminated from the test list if the relations between EVM and system impairments are derived independent of the circuit implementation and manufacturing process. In this work, the focus is on the WLAN standard, and deriving the relations between EVM and three of the most detrimental impairments for QAM/OFDM based systems (IQ imbalance, non-linearity, and noise). Having low cost test techniques for measuring the RF transceivers imperfections and being able to analytically compute EVM from the measured parameters is a complete test solution for RF transceivers. These techniques along with the proposed calibration method can be used in improving the yield by widening the pass/fail boundaries for transceivers imperfections. For all of the proposed methods, simulation and hardware measurements prove that the proposed techniques provide accurate characterization of RF transceivers.
ContributorsNassery, Afsaneh (Author) / Ozev, Sule (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Kiaei, Sayfe (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sliding-Mode Control (SMC) has several benefits over traditional Proportional-Integral-Differential (PID) control in terms of fast transient response, robustness to parameter and component variations, and low sensitivity to loop disturbances. An All-Digital Sliding-Mode (ADSM) controlled DC-DC converter, utilizing single-bit oversampled frequency domain digitizers is proposed. In the proposed approach, feedback and reference digitizing Analog-to-Digital Converters (ADC) are based on a single-bit, first order Sigma-Delta frequency to digital converter, running at 32MHz over-sampling rate. The ADSM regulator achieves 1% settling time in less than 5uSec for a load variation of 600mA. The sliding-mode controller utilizes a high-bandwidth hysteretic differentiator and an integrator to perform the sliding control law in digital domain. The proposed approach overcomes the steady state error (or DC offset), and limits the switching frequency range, which are the two common problems associated with sliding-mode controllers. The IC is designed and fabricated on a 0.35um CMOS process occupying an active area of 2.72mm-squared. Measured peak efficiency is 83%.
ContributorsDashtestani, Ahmad (Author) / Bakkaloglu, Bertan (Thesis advisor) / Thornton, Trevor (Committee member) / Song, Hongjiang (Committee member) / Kiaei, Sayfe (Committee member) / Arizona State University (Publisher)
Created2013
Description
Electrical neural activity detection and tracking have many applications in medical research and brain computer interface technologies. In this thesis, we focus on the development of advanced signal processing algorithms to track neural activity and on the mapping of these algorithms onto hardware to enable real-time tracking. At the heart of these algorithms is particle filtering (PF), a sequential Monte Carlo technique used to estimate the unknown parameters of dynamic systems. First, we analyze the bottlenecks in existing PF algorithms, and we propose a new parallel PF (PPF) algorithm based on the independent Metropolis-Hastings (IMH) algorithm. We show that the proposed PPF-IMH algorithm improves the root mean-squared error (RMSE) estimation performance, and we demonstrate that a parallel implementation of the algorithm results in significant reduction in inter-processor communication. We apply our implementation on a Xilinx Virtex-5 field programmable gate array (FPGA) platform to demonstrate that, for a one-dimensional problem, the PPF-IMH architecture with four processing elements and 1,000 particles can process input samples at 170 kHz by using less than 5% FPGA resources. We also apply the proposed PPF-IMH to waveform-agile sensing to achieve real-time tracking of dynamic targets with high RMSE tracking performance. We next integrate the PPF-IMH algorithm to track the dynamic parameters in neural sensing when the number of neural dipole sources is known. We analyze the computational complexity of a PF based method and propose the use of multiple particle filtering (MPF) to reduce the complexity. We demonstrate the improved performance of MPF using numerical simulations with both synthetic and real data. We also propose an FPGA implementation of the MPF algorithm and show that the implementation supports real-time tracking. For the more realistic scenario of automatically estimating an unknown number of time-varying neural dipole sources, we propose a new approach based on the probability hypothesis density filtering (PHDF) algorithm. The PHDF is implemented using particle filtering (PF-PHDF), and it is applied in a closed-loop to first estimate the number of dipole sources and then their corresponding amplitude, location and orientation parameters. We demonstrate the improved tracking performance of the proposed PF-PHDF algorithm and map it onto a Xilinx Virtex-5 FPGA platform to show its real-time implementation potential. Finally, we propose the use of sensor scheduling and compressive sensing techniques to reduce the number of active sensors, and thus overall power consumption, of electroencephalography (EEG) systems. We propose an efficient sensor scheduling algorithm which adaptively configures EEG sensors at each measurement time interval to reduce the number of sensors needed for accurate tracking. We combine the sensor scheduling method with PF-PHDF and implement the system on an FPGA platform to achieve real-time tracking. We also investigate the sparsity of EEG signals and integrate compressive sensing with PF to estimate neural activity. Simulation results show that both sensor scheduling and compressive sensing based methods achieve comparable tracking performance with significantly reduced number of sensors.
ContributorsMiao, Lifeng (Author) / Chakrabarti, Chaitali (Thesis advisor) / Papandreou-Suppappola, Antonia (Thesis advisor) / Zhang, Junshan (Committee member) / Bliss, Daniel (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Immunosignaturing is a medical test for assessing the health status of a patient by applying microarrays of random sequence peptides to determine the patient's immune fingerprint by associating antibodies from a biological sample to immune responses. The immunosignature measurements can potentially provide pre-symptomatic diagnosis for infectious diseases or detection of biological threats. Currently, traditional bioinformatics tools, such as data mining classification algorithms, are used to process the large amount of peptide microarray data. However, these methods generally require training data and do not adapt to changing immune conditions or additional patient information. This work proposes advanced processing techniques to improve the classification and identification of single and multiple underlying immune response states embedded in immunosignatures, making it possible to detect both known and previously unknown diseases or biothreat agents. Novel adaptive learning methodologies for un- supervised and semi-supervised clustering integrated with immunosignature feature extraction approaches are proposed. The techniques are based on extracting novel stochastic features from microarray binding intensities and use Dirichlet process Gaussian mixture models to adaptively cluster the immunosignatures in the feature space. This learning-while-clustering approach allows continuous discovery of antibody activity by adaptively detecting new disease states, with limited a priori disease or patient information. A beta process factor analysis model to determine underlying patient immune responses is also proposed to further improve the adaptive clustering performance by formatting new relationships between patients and antibody activity. In order to extend the clustering methods for diagnosing multiple states in a patient, the adaptive hierarchical Dirichlet process is integrated with modified beta process factor analysis latent feature modeling to identify relationships between patients and infectious agents. The use of Bayesian nonparametric adaptive learning techniques allows for further clustering if additional patient data is received. Significant improvements in feature identification and immune response clustering are demonstrated using samples from patients with different diseases.
ContributorsMalin, Anna (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Bliss, Daniel (Committee member) / Chakrabarti, Chaitali (Committee member) / Kovvali, Narayan (Committee member) / Lacroix, Zoé (Committee member) / Arizona State University (Publisher)
Created2013
Description
During the last decades the development of the transistor and its continuous down-scaling allowed the appearance of cost effective wireless communication systems. New generation wideband wireless mobile systems demand high linearity, low power consumption and the low cost devices. Traditional RF systems are mainly analog-based circuitry. Contrary to digital circuits, the technology scaling results in reduction on the maximum voltage swing which makes RF design very challenging. Pushing the interface between the digital and analog boundary of the RF systems closer to the antenna becomes an attractive trend for modern RF devices. In order to take full advantages of the deep submicron CMOS technologies and digital signal processing (DSP), there is a strong trend towards the development of digital transmitter where the RF upconversion is part of the digital-to-analog conversion (DAC). This thesis presents a new digital intermediate frequency (IF) to RF transmitter for 2GHz wideband code division multiple access (W-CDMA). The proposed transmitter integrates a 3-level digital IF current-steering cell, an up-conversion mixer with a tuned load and an RF variable gain amplifier (RF VGA) with an embedded finite impulse response (FIR) reconstruction filter in the up-conversion path. A 4th-order 1.5-bit IF bandpass sigma delta modulator (BP SDM) is designed to support in-band SNR while the out-of-band quantization noise due to the noise shaping is suppressed by the embedded reconstruction filter to meet spectrum emission mask and ACPR requirements. The RF VGA provides 50dB power scaling in 10-dB steps with less than 1dB gain error. The design is fabricated in a 0.18um CMOS technology with a total core area of 0.8 x 1.6 mm2. The IC delivers 0dBm output power at 2GHz and it draws approximately 120mA from a 1.8V DC supply at the maximum output power. The measurement results proved that a digital-intensive digital IF to RF converter architecture can be successfully employed for WCDMA transmitter application.
ContributorsHan, Yongping (Author) / Kiaei, Sayfe (Thesis advisor) / Yu, Hongyu (Committee member) / Bakkaloglu, Bertan (Committee member) / Aberle, James T., 1961- (Committee member) / Barnaby, Hugh (Committee member) / Arizona State University (Publisher)
Created2012