Low harmonic distortion flash A/D converters incorporating dynamic element matching techniques

New dynamic element matching techniques are shown to reduce the harmonic distortion and improve the spurious-free dynamic range of flash ADCs. Resistor chain mismatch errors are negated by randomly rearranging the resistors each sample by utilizing 5(2{dollar}\sp{b}{dollar}-1) digital switches and b + 1 random control signals for a b-bit flash ADC. The integral and differential nonlinearity of a non-ideal flash ADC are derived for three common resistor chain mismatch errors; namely, geometric mismatches, linear gradient mismatches, and dynamic mismatches. The transfer function of a non-ideal flash ADC is also derived and the converter output is shown to consist of a scaled copy of the input, a DC gain, and conversion noise that is a function of the resistor mismatches. A comprehensive summary of dynamic element matching techniques given in literature is provided. In addition, the DEM network introduced by Galton and Jensen is shown to be equivalent to the generalized-cube network used in parallel processing architectures. An alternative version of this network that uses logic gates is also proposed

Dynamic element matching techniques for data converters

Analog to digital converter (ADC) circuit component errors create nonuniform quantization code widths and create harmonic distortion in an ADC\u27s output. In this dissertation, two techniques for estimating an ADC\u27s output spectrum from the ADC\u27s transfer function are determined. These methods are compared to a symmetric power function and asymmetric power function approximations. Standard ADC performance metrics, such as SDR, SNDR, SNR, and SFDR, are also determined as a function of the ADC\u27s transfer function approximations. New dynamic element matching (DEM) flash ADCs are developed. An analysis of these DEM flash ADCs is developed and shows that these DEM algorithms improve an ADC\u27s performance. The analysis is also used to analyze several existing DEM ADC architectures; Digital to analog converter (DAC) circuit component errors create nonuniform quantization code widths and create harmonic distortion in a DAC\u27s output. In this dissertation, an exact relationship between a DAC\u27s integral nonlinearity (INL) and its output spectrum is determined. Using this relationship, standard DAC performance metrics, such as SDR, SNDR, SNR, and SFDR, are calculated from the DAC\u27s transfer function. Furthermore, an iterative method is developed which determines an arbitrary DAC\u27s transfer function from observed output magnitude spectra. An analysis of DEM techniques for DACs, including the determination of several suitable metrics by which DEM techniques can be compared, is derived. The performance of a given DEM technique is related to standard DAC performance metrics, such as SDR, SNDR, and SFDR. Conditions under which DEM techniques can guarantee zero average INL and render the distortion due to mismatched components as white noise are developed. Several DEM circuits proposed in the literature are shown to be equivalent and have hardware efficient implementations based on multistage interconnection networks. Example DEM circuit topologies and their hardware efficient VLSI implementations are also presented

Energy-efficient analog-to-digital conversion for ultra-wideband radio

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 207-222).In energy constrained signal processing and communication systems, a focus on the analog or digital circuits in isolation cannot achieve the minimum power consumption. Furthermore, in advanced technologies with significant variation, yield is traditionally achieved only through conservative design and a sacrifice of energy efficiency. In this thesis, these limitations are addressed with both a comprehensive mixed-signal design methodology and new circuits and architectures, as presented in the context of an analog-to-digital converter (ADC) for ultra-wideband (UWB) radio. UWB is an emerging technology capable of high-data-rate wireless communication and precise locationing, and it requires high-speed (>500MS/s), low-resolution ADCs. The successive approximation register (SAR) topology exhibits significantly reduced complexity compared to the traditional flash architecture. Three time-interleaved SAR ADCs have been implemented. At the mixed-signal optimum energy point, parallelism and reduced voltage supplies provide more than 3x energy savings. Custom control logic, a new capacitive DAC, and a hierarchical sampling network enable the high-speed operation. Finally, only a small amount of redundancy, with negligible power penalty, dramatically improves the yield of the highly parallel ADC in deep sub-micron CMOS.by Brian P. Ginsburg.Ph.D

Digital Background Self-Calibration Technique for Compensating Transition Offsets in Reference-less Flash ADCs

This Dissertation focusses on proving that background calibration using adaptive algorithms are low-cost, stable and effective methods for obtaining high accuracy in flash A/D converters. An integrated reference-less 3-bit flash ADC circuit has been successfully designed and taped out in UMC 180 nm CMOS technology in order to prove the efficiency of our proposed background calibration. References for ADC transitions have been virtually implemented built-in in the comparators dynamic-latch topology by a controlled mismatch added to each comparator input front-end. An external very simple DAC block (calibration bank) allows control the quantity of mismatch added in each comparator front-end and, therefore, compensate the offset of its effective transition with respect to the nominal value. In order to assist to the estimation of the offset of the prototype comparators, an auxiliary A/D converter with higher resolution and lower conversion speed than the flash ADC is used: a 6-bit capacitive-DAC SAR type. Special care in synchronization of analogue sampling instant in both ADCs has been taken into account. In this thesis, a criterion to identify the optimum parameters of the flash ADC design with adaptive background calibration has been set. With this criterion, the best choice for dynamic latch architecture, calibration bank resolution and flash ADC resolution are selected. The performance of the calibration algorithm have been tested, providing great programmability to the digital processor that implements the algorithm, allowing to choose the algorithm limits, accuracy and quantization errors in the arithmetic. Further, systematic controlled offset can be forced in the comparators of the flash ADC in order to have a more exhaustive test of calibration

Design and debugging of multi-step analog to digital converters

With the fast advancement of CMOS fabrication technology, more and more signal-processing functions are implemented in the digital domain for a lower cost, lower power consumption, higher yield, and higher re-configurability. The trend of increasing integration level for integrated circuits has forced the A/D converter interface to reside on the same silicon in complex mixed-signal ICs containing mostly digital blocks for DSP and control. However, specifications of the converters in various applications emphasize high dynamic range and low spurious spectral performance. It is nontrivial to achieve this level of linearity in a monolithic environment where post-fabrication component trimming or calibration is cumbersome to implement for certain applications or/and for cost and manufacturability reasons. Additionally, as CMOS integrated circuits are accomplishing unprecedented integration levels, potential problems associated with device scaling – the short-channel effects – are also looming large as technology strides into the deep-submicron regime. The A/D conversion process involves sampling the applied analog input signal and quantizing it to its digital representation by comparing it to reference voltages before further signal processing in subsequent digital systems. Depending on how these functions are combined, different A/D converter architectures can be implemented with different requirements on each function. Practical realizations show the trend that to a first order, converter power is directly proportional to sampling rate. However, power dissipation required becomes nonlinear as the speed capabilities of a process technology are pushed to the limit. Pipeline and two-step/multi-step converters tend to be the most efficient at achieving a given resolution and sampling rate specification. This thesis is in a sense unique work as it covers the whole spectrum of design, test, debugging and calibration of multi-step A/D converters; it incorporates development of circuit techniques and algorithms to enhance the resolution and attainable sample rate of an A/D converter and to enhance testing and debugging potential to detect errors dynamically, to isolate and confine faults, and to recover and compensate for the errors continuously. The power proficiency for high resolution of multi-step converter by combining parallelism and calibration and exploiting low-voltage circuit techniques is demonstrated with a 1.8 V, 12-bit, 80 MS/s, 100 mW analog to-digital converter fabricated in five-metal layers 0.18-µm CMOS process. Lower power supply voltages significantly reduce noise margins and increase variations in process, device and design parameters. Consequently, it is steadily more difficult to control the fabrication process precisely enough to maintain uniformity. Microscopic particles present in the manufacturing environment and slight variations in the parameters of manufacturing steps can all lead to the geometrical and electrical properties of an IC to deviate from those generated at the end of the design process. Those defects can cause various types of malfunctioning, depending on the IC topology and the nature of the defect. To relive the burden placed on IC design and manufacturing originated with ever-increasing costs associated with testing and debugging of complex mixed-signal electronic systems, several circuit techniques and algorithms are developed and incorporated in proposed ATPG, DfT and BIST methodologies. Process variation cannot be solved by improving manufacturing tolerances; variability must be reduced by new device technology or managed by design in order for scaling to continue. Similarly, within-die performance variation also imposes new challenges for test methods. With the use of dedicated sensors, which exploit knowledge of the circuit structure and the specific defect mechanisms, the method described in this thesis facilitates early and fast identification of excessive process parameter variation effects. The expectation-maximization algorithm makes the estimation problem more tractable and also yields good estimates of the parameters for small sample sizes. To allow the test guidance with the information obtained through monitoring process variations implemented adjusted support vector machine classifier simultaneously minimize the empirical classification error and maximize the geometric margin. On a positive note, the use of digital enhancing calibration techniques reduces the need for expensive technologies with special fabrication steps. Indeed, the extra cost of digital processing is normally affordable as the use of submicron mixed signal technologies allows for efficient usage of silicon area even for relatively complex algorithms. Employed adaptive filtering algorithm for error estimation offers the small number of operations per iteration and does not require correlation function calculation nor matrix inversions. The presented foreground calibration algorithm does not need any dedicated test signal and does not require a part of the conversion time. It works continuously and with every signal applied to the A/D converter. The feasibility of the method for on-line and off-line debugging and calibration has been verified by experimental measurements from the silicon prototype fabricated in standard single poly, six metal 0.09-µm CMOS process

Evaluation of EEG-based depth of anaesthesia monitoring

In 2001 a University of Bristol team patented a novel data reduction method of the EEG for characterising categorical changes in consciousness. After pre-whitening the EEG signal with Gaussian white noise a parametric spectral estimation technique was applied. Two frequency domain indices were then proposed: the relative power found between 8Hz to 12Hz and 0.5Hz to 32Hz termed the 'alpha index', and the relative power between 0.5Hz to 4Hz and 0.5Hz to 32Hz termed the 'delta index'. The research and development of a precision EEG monitoring device designed to embody the novel algorithm is described in this thesis. The efficacy of the technique was evaluated using simulated and real EEG data recorded during Propofol anaesthesia. The simulated data showed improvements could be made to the patented method. Real EEG data collected whilst patients were wakeful and data from patients unresponsive to noxious stimuli were cleaned of obvious artefacts and analysed using the proposed algorithm. A Bayesian diagnostic test showed the alpha index had 65% sensitivity and selectivity to patient state. The delta index showed 72% sensitivity and selectivity. Taking a pragmatic approach, the literature is reviewed in this thesis to evaluate the use of EEG in depth of anaesthesia monitoring. Pertinent aspects of the sciences are profiled to identify physiological links to the characteristics of the EEG signal. Methods of data reduction are also reviewed to identify useful features and possible sources of error. In conclusion it is shown that the proposed indices do not provide a robust measure of depth of anaesthesia. An approach for further research is proposed based on the review work.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

The Machine that Lives Forever

Design an intelligent micromachine that can self-power and sustain from environmental energy scavenging to achieve an autonomous device that can communicate at will with peers indefinitely. Explore sleep/wake hibernation strategies coupled with food scavenging off-grid traits to identify the tightest work to sleep efficiency schedule, incorporating adaptive reconfiguration to manage significant environmental impacts. Capture, store and manage background radiations and stray RF signals to feed on in a continued effort to make intelligent survival decisions and oversee management protocols. Ensure that every micro Watt of usable energy gets extracted from every part of the harvest and then forward-scheduled it for productive use. Finally, employ natures tricks and experience to introduce essential personality traits, pursuing maximising survival numbers and increasing dispersal target area sizes of large self-sufficient wireless sensor deployments. This research intends to provide a closely coupled software-hardware foundation that aids implementers in intelligently harnessing and using tiny amounts of ambient energy in a highly autonomous way. This platform then continues on to explore ways of maximising the efficient usage of the harvested energy using various hibernation/wake strategies and then making objective comparisons with proposed intelligent energy management protocols. Finally, the protocol extends to enable the device to manage its personal survival possibilities so the devices can use an evolutional personality-based approach to deal with the unknown environmental situations they will encounter. This work examines a machine that can self-power and sustain from environmental energy scavenging with the aim to live forever. Living forever implies a brain (microcontroller) that can manage energy and budget for continuous faculty. With these objectives, sleep/wake/hibernation and scavenging strategies are examined to efficiently schedule resources within a transient environment. Example harvesting includes induced and background radiation. Intelligent, biologically-inspired strategies are adopted in forward-scheduling strategies given temporal energy relative to the machine’s function (the Walton)