Book•
Understanding Delta-Sigma Data Converters
08 Nov 2004-
TL;DR: This chapter discusses the design and simulation of delta-sigma modulator systems, and some of the considerations for implementation considerations for [Delta][Sigma] ADCs.
Abstract: Chapter 1: Introduction.Chapter 2: The first-order delta-sigma modulator.Chapter 3: The second-order delta-sigma modulator.Chapter 4: Higher-order delta-sigma modulation.Chapter 5: Bandpass and quadrature delta-sigma modulation.Chapter 6: Implementation considerations for [Delta][Sigma] ADCs.Chapter 7: Delta-sigma DACs.Chapter 8: High-level design and simulation.Chapter 9: Example modulator systems.Appendix A: Spectral estimation.Appendix B: The delta-sigma toolbox.Appendix C: Noise in switched-capacitor delta-sigma data converters.
Citations
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TL;DR: A self-calibration algorithm is focused on that helps minimize the quantization noise of the EFBD and helps to flatten the signal transfer function.
Abstract: Frequency-band-decomposition (FBD) is a good candidate to be used to increase the bandwidths of ADC converters based on sigma-delta modulators for software and cognitive radio applications where we need to convert wide bandwidths. Each modulator processes a part of the band of the input signal which is then passed through a digital filter. In the case of large mismatches in the analog modulators, a new solution, called extended frequency-band-decomposition (EFBD) can be used. As an example, this solution can allow for a 4% error in the central frequencies without significant degradation of its performance when the digital processing part is paired with the analog modulators. A calibration of the digital part is thus required to reach these theoretical performances. This paper will focus on a self-calibration algorithm for an EFBD. The algorithm helps minimize the quantization noise of the EFBD and helps to flatten the signal transfer function.
3 citations
Cites background from "Understanding Delta-Sigma Data Conv..."
...The expected performance of each modulator can be evaluated from the in-band noise power given by [4]:...
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...The Frequency-Band-Decomposition (FBD) [1], [2], [3] is a natural way to widen the bandwidth of sigma-delta converters [4], using parallel bandpass modulators, where each modulator processes a part of the band of the input signal [5]....
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01 Oct 2015
TL;DR: The design of a Finite Impulse Response Filter based on Delta Sigma Signal Processing achieves a Θ(N) complexity with N inputs and can work with higher-order Delta Sigma bit-streams.
Abstract: This paper presents the design of a Finite Impulse Response Filter based on Delta Sigma Signal Processing. Both input and output of the proposed circuit are encoded as second-order Delta Sigma bit-streams. The design is realized using a Delta Sigma adder based on an input counter. The Delta Sigma adder can also be used as a coefficient multiplier. Using the proposed Delta Sigma adder and coefficient multiplier, an Finite Impulse Response filter is designed for Electroencephalogram signal processing. Simulation and synthesis results are shown based on IBM 180nm CMOS technology. The proposed design achieves a Θ(N) complexity with N inputs and can work with higher-order Delta Sigma bit-streams.
3 citations
Cites background or methods from "Understanding Delta-Sigma Data Conv..."
...First, compared to a Nyquist rate ADC, a DSM based oversampling ADC can achieve higher resolution using less circuitry and power [4]....
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...Second, resolution of an oversampling system is adjustable by changing the sampling frequency at the input after fabrication [4]....
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06 Nov 2009
TL;DR: In this paper, a delta-sigma pulse modulation AC-DC power converter with AC-boost DC and Boost-DC-Buck DC two-stage circuit topologies is evaluated.
Abstract: A high frequency carrier PWM regulator used for various types of switch-mode power converters are based on the digital or analog signal comparison processing. The voltage-mode or current-mode PWM strategies due to comparison signal processing between voltage / current reference and periodic carrier signals cause the switching noise peaks dependent on the multiple numbers of carrier signal frequency. In general, the switching noise peaks are actually difficult to remove. On the other hand, the utility AC grid side AC-DC converter with the cascaded DC-DC converter stage includes low frequency components of its line current. This paper deals with a delta-sigma pulse modulation AC-DC power converter with AC-boost DC and Boost-DC-Buck DC two-stage circuit topologies. This AC-DC converter with boost-buck circuit topology includes the switching noise peaks characteristic of the output DC voltage as well as utility AC grid side harmonic current components suppression characteristic. The effectiveness of two stage boost-buck AC-DC converter controlled by current-mode delta-sigma and voltage-mode delta-sigma pulse modulation schemes is verified by evaluation as compared with PWM-based AC-DC converter about the utility AC current and switching noise peaks of the output voltage performances.
3 citations
Cites background from "Understanding Delta-Sigma Data Conv..."
...Generally, the quantization error noise arises uniformly to frequency, error noise distribution changes through using delta-sigma modulator [2], [3]....
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TL;DR: A second-order 3-bit incremental converter, which employs a novel Smart-DEM algorithm to compensate for the mismatch among unity elements of the multi-level digital-to-analog converter is described in this article.
Abstract: AlessandroDAmato@ticomThis paper describes a second-order 3-bit incremental converter, which employs a novel Smart-DEM algorithm to compensate for the mismatch among unity elements of the multi-level digital-to-analog converter The design, which is fabricated in a mixed 018---05 $$\upmu$$μm CMOS technology, achieves 167-bit resolution over a 5-kHz bandwidth by using 256 clock periods per sample A single-step chopping technique leads to a residual offset of 97 $$\upmu$$μV The measured power consumption is 280 $$\upmu$$μW and the achieved figure of merit is 17495 dB
3 citations
19 Jul 2020
TL;DR: The problem of reconstructing a complex-valued signal from its phase-only measurements is considered and the proposed formalism applies to a broader class of signals, obtaining high accuracy for reconstructing 1–D synthetic signals in the absence of noise.
Abstract: We consider the problem of reconstructing a complex-valued signal from its phase-only measurements. This framework can be considered as a generalization of the well-known one-bit compressed sensing paradigm where the underlying signal is known to be sparse. In contrast, the proposed formalism does not rely on the assumption of sparsity and hence applies to a broader class of signals. The optimization problem for signal reconstruction is formulated by first splitting the linear measurement vector into its phase and magnitude components and subsequently using the non-negativity property of the magnitude component as a constraint. The resulting optimization problem turns out to be a quadratic program (QP) and is solved using two algorithms: (i) alternating directions method of multipliers; and (ii) projected gradient-descent with Nesterov’s momentum. Due to the inherent scale ambiguity of the phase-only measurement, the underlying signal can be reconstructed only up to a global scale-factor. We obtain high accuracy for reconstructing 1–D synthetic signals in the absence of noise. We also show an application of the proposed approach in reconstructing images from the phase of their measurement coefficients. The underlying image is recovered up to a peak signal-to-noise ratio exceeding 30 dB in several examples, indicating an accurate reconstruction.
3 citations
Cites methods from "Understanding Delta-Sigma Data Conv..."
...For example, in sigma-delta converters [1], the signal is sampled at a rate much higher than the Nyquist rate but is coarsely encoded using onebit quantization, whereas in compressed sensing (CS) [2], the sparsity prior is exploited to recover the signal from its lowdimensional linear projection....
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References
More filters
TL;DR: Higher order modulators are shown not only to greatly reduce oversampling requirements for high-resolution conversion applications, but also to randomize the quantization noise, avoiding the need for dithering.
Abstract: Oversampling interpolative coding has been demonstrated to be an effective technique for high-resolution analog-to-digital (A/D) conversion that is tolerant of process imperfections. A novel topology for constructing stable interpolative modulators of arbitrary order is described. Analysis of this topology shows that with proper design of the modulator coefficients, stability is not a limitation to higher order modulators. Furthermore, complete control over placement of the poles and zeros of the quantization noise response allows treatment of the modulation process as a high-pass filter for quantization noise. Higher order modulators are shown not only to greatly reduce oversampling requirements for high-resolution conversion applications, but also to randomize the quantization noise, avoiding the need for dithering. An experimental fourth-order modulator breadboard demonstrates stability and feasibility, achieving a 90-dB dynamic range over the 20-kHz audio bandwidth with a sampling rate of 2.1 MHz. A generalized simulation software package has been developed to mimic time-domain behavior for oversampling modulators. Circuit design specifications for integrated circuit implementation can be deduced from analysis of simulated data. >
399 citations
TL;DR: It is shown that digital filters comprising cascades of integrate-and-dump functions can match the structure of the noise from sigma delta modulation to provide decimation with negligible loss of signal-to-noise ratio.
Abstract: Decimation is an important component of oversampled analog-to-digital conversion. It transforms the digitally modulated signal from short words occurring at high sampling rate to longer words at the Nyquist rate. Here we are concerned with the initial stage of decimation, where the word rate decreases to about four times the Nyquist rate. We show that digital filters comprising cascades of integrate-and-dump functions can match the structure of the noise from sigma delta modulation to provide decimation with negligible loss of signal-to-noise ratio. Explicit formulas evaluate particular tradeoffs between modulation rate, signal-to-noise ratio, length of digital words, and complexity of the modulating and decimating functions.
342 citations
TL;DR: This paper introduces a new method of analysis for deltasigma modulators based on modeling the nonlinear quantizer with a linearized gain, obtained by minimizing a mean-square-error criterion, followed by an additive noise source representing distortion components.
Abstract: This paper introduces a new method of analysis for deltasigma modulators based on modeling the nonlinear quantizer with a linearized gain, obtained by minimizing a mean-square-error criterion [7], followed by an additive noise source representing distortion components. In the paper, input signal amplitude dependencies of delta-sigma modulator stability and signal-to-noise ratio are analyzed. It is shown that due to the nonlinearity of the quantizer, the signal-to-noise ratio of the modulator may decrease as the input amplitude increases prior to saturation. Also, a stable third-order delta-sigma modulator may become unstable by increasing the input amplitude beyond a certain threshold. Both of these phenomena are explained by the nonlinear analysis of this paper. The analysis is carried out for both dc and sinusoidal excitations.
284 citations
TL;DR: Simple algebraic expressions for this modulation noise and its spectrum in terms of the input amplitude are derived and can be useful for designing oversampled analog to digital converters that use sigma-delta modulation for the primary conversion.
Abstract: When the sampling rate of a sigma-delta modulator far exceeds the frequencies of the input signal, its modulation noise is highly correlated with the amplitude of the input. We derive simple algebraic expressions for this noise and its spectrum in terms of the input amplitude. The results agree with measurements taken on a breadboard circuit. This work can be useful for designing oversampled analog to digital converters that use sigma-delta modulation for the primary conversion.
255 citations
01 Mar 1993
TL;DR: The modulator of a bandpass analog/digital (A/D) converter, with 63 dB signal/noise for broadcast AM bandwidth signals centered at 455 kHz, has been implemented by modifying a commercial digital-audio sigma-delta ( Sigma Delta ) converter.
Abstract: The modulator of a bandpass analog/digital (A/D) converter, with 63 dB signal/noise for broadcast AM bandwidth signals centered at 455 kHz, has been implemented by modifying a commercial digital-audio sigma-delta ( Sigma Delta ) converter. It is the first reported fully monolithic implementation of bandpass noise shaping and has applications to digital radio. >
211 citations