Edward W. Y. Liu

Behavioral simulation techniques for phase/delay-locked systems

This paper presents behavioral simulation techniques for phase/delay-locked systems. Numerical simulation algorithms are compared and the issue of numerical noise is discussed. Behavioral phase noise simulation for phase/delay-locked systems is described. The role of behavioral simulation for phase/delay-locked systems in our top-down constraint-driven design methodology, and in bottom-up verification of designs, is explained with examples. Accuracy and efficiency comparisons with other methods are made. Simulation techniques are described in the framework of phase/delay-locked systems, but simulation methodology and the results attained in this work are applicable to the behavioral simulation of mixed-mode nonlinear dynamic systems.<<ETX>>

Behavioral modeling and simulation of data converters

The authors present a behavioral representation for the class of Nyquist rate analog to digital (A/D) converters that captures the nominal behavior, as well as all the statistical variations. To describe behavioral effects due to process variations a covariance matrix, Sigma /sub t/ is used. Applications of the model include identification of important A/D error sources, efficient computation of the distributions of integral nonlinearity and differential nonlinearity, signal-to-noise plus distortion ratio and efficient worst case and Monte Carlo system simulations. Parameter extraction results are presented that agree well with actual measurements.<<ETX>>

A behavioral representation for Nyquist rate A/D converters

The authors present a behavioral representation for the class of Nyquist rate A/D (analog-to-digital) converters. The representation captures the nominal A/D behavior as well as all the statistical variations. The variations are classified into noise and process variations according to how these nonidealities affect the A/D behavior. To describe noise effects a joint probability density function is used. To describe behavioral effects due to process variations, use is made of a variance-covariance matrix, Sigma /sub t/, which is a generalization of the integral nonlinearity vector. Sigma /sub t/s rank characterizes the testability of an A/D; its decomposition yields efficient strategies for A/D testing. Finally, parameter extraction results obtained from prototypes are presented.<<ETX>>

Behavioral Representations For VCO And Detectors In Phase-lock Systems

This paper presents behavioral representations for detectors and voltage-controlled oscillators that are independent of circuit architectures. Parameter extraction techniques are described. Finally, parameter extraction for a VCO is demonstrated, and an example PLL constructed using the models is simulated and verified against actual chip measurements.

Top-down, constraint-driven design methodology based generation of n-bit interpolative current source D/A converters

To accelerate the design cycle for analog circuits and mixed-signal systems, we have proposed a top-down, constraint-driven design methodology. In this paper we present a design which demonstrates the two principal advantages that this methodology provides- a high probability for first silicon which meets all specifications and fast design times. We examine the design of three different 10-bit digital-to-analog (D/A) converters beginning from their performance and functional specifications and ending with the testing of the fabricated parts. Critical technology mismatch information gathered from the testing phase is provided.<<ETX>>

Verification of Nyquist data converters using behavioral simulation

A behavioral representation of Nyquist data converters is presented. The representation captures the static behavior of a memoryless Nyquist data converter including statistical variations. The variations are classified into noise and process variations according to how these nonidealities affect the converter behavior. To describe noise effects, a joint probability density function is used. To describe behavioral effects due to process variations, a Gaussian model is used. Using the behavioral representation, a novel strategy to calculate system performance is developed. The performance specifications of a converter, including offset error, full scale gain error, integral nonlinearity, differential nonlinearity, harmonic distortion, and signal-to-noise ratio, are calculated in two steps. First, the converter model parameters are extracted from the circuit. Then, the converter performance is computed using only the model parameters since the model captures the converter behavior. Experimental results agree well with SPICE simulations and confirm the validity of the model. >

A Top-down, Constraint-Driven Design Methodology for Analog Integrated Circuits

This paper describes a top-down, constraint-driven design methodology for analog integrated circuits. Some of the tools that support this methodology are described. These include behavioral simulation tools, tools for physical assembly, and module generators. Finally, examples of behavioral simulation with optimization and physical assembly are provided to better illustrate the methodology and its integration with the tool set.

Analog System Verification in the Presence of Parasitics Using Behavioral Simulation

In analog system design, final verification in the presence of parasitic loading effects is crucial to guarantee functionality of the entire circuit. In this paper, we present a methodology for analog system verification in the presence of parasitics using behavioral simulation. When applied to a synthesized 10 bit D/A, our approach is accurate to 0.005 LSB compared with SPICE, while being several orders of magnitude faster.

Analog behavioral models for simulation and synthesis of mixed-signal systems

A behavioral simulator is shown to be an essential part of a performance-driven hierarchical top-down design strategy for analog blocks within mixed-signal integrated systems. It is used to accurately estimate the performance of the system while down-mapping the specifications over the hierarchy, in order to avoid time-consuming design iterations. It is also indispensable for the final bottom-up verification after completion of the design, as well as for testing purposes. The authors describe the set-up of the generic behavioral models for this simulator, which describe the functional behavior of the analog blocks, independent of the internal architecture. In addition to the nominal behavior, the models also include the important second-order effects (nonidealities, noise, distortion . . .) as well as the statistical variations of most parameters. This is then illustrated in detail for the statistical minimum-rank model of a Nyquist-rate A/D converter. System-level applications show the effectiveness and accuracy of this model.<<ETX>>

Behavioral simulation for noise in mixed-mode sampled-data systems

A direct noise analysis approach for mixed-mode systems is presented with experimental results compared with results from the traditional Monte Carlo approach. The direct approach computes noise effects by performing arithmetic on moments of distribution functions that characterize electronic noise. One key advantage of this approach is its ability to compute low error probabilities. From experimental results, it is shown that very low order moments, such as second order, are sufficient for a good estimate of noise effects.<<ETX>>