Abstract: In one embodiment, a spectral map for performing nonlinear calibration of a signal path is developed by 1) identifying a set of frequency locations for a set of particular output signal spurs that result from applying one-tone and two-tone input signals covering a bandwidth of interest to the signal path; 2) developing, based on the set of frequency locations, a spectral map for predistorting, in the frequency domain, signals that are applied to, or received from, the signal path in the time domain; and 3) saving the spectral map for performing nonlinear calibration of the signal path.

Abstract: In one embodiment, a spectral map for performing nonlinear calibration of a signal path is developed by 1) identifying a set of frequency locations for a set of particular output signal spurs that result from applying one-tone and two-tone input signals covering a bandwidth of interest to the signal path; 2) developing, based on the set of frequency locations, a spectral map for predistorting, in the frequency domain, signals that are applied to, or received from, the signal path in the time domain; and 3) saving the spectral map for performing nonlinear calibration of the signal path.

Abstract: The model-based method tests compliance of production devices with the performance specifications of a device design. The production devices are manufactured in accordance with the device design by a manufacturing process. In the method, a simple model form based on the device design and the performance specifications is developed, a stimulus for testing the production devices is specified and each production device is tested. The model form has a basis function and model form parameters for the basis function. The model form parameters are dependent on the manufacturing process and differ in value among the production devices. A production device is tested by measuring the response of the production device to the stimulus; extracting, using the model form, the values of the model form parameters for the production device from the measured response and the stimulus; and checking compliance of the production device with the performance specifications using the extracted values of the model form parameters.

Abstract: A testing system and various methods involving testing of a device under test (DUT) use a device model to model a stimulus-response behavior of a the DUT. The testing system includes a device model of the DUT that is fitted to the stimulus-response behavior of the DUT and a measurement projector connected to an output of the device model. The device model includes a block diagram model and a difference model. Test metrics for the DUT are produced by the measurement projector from an output of the fitted device model.

Abstract: A system and a general method estimate figures of merit based on nonlinear modeling and nonlinear time series analysis. Terms in a nonlinear behavioral model that depend on nonlinear combinations of a fixed input signal value are precomputed, optimizing the behavioral model such that figures of merit are evaluated from a single short stimulus vector. The optimized nonlinear behavioral model can then be applied to evaluate figures of merit for multiple devices under test (DUTs) in a manufacturing line. A process continually verifies and adjusts the nonlinear behavioral model based on sub-sampling multiple DUTs in a manufacturing line and comparing their figures of merit based on nonlinear modeling with those based on conventional measurement procedures.

Abstract: A method and apparatus that utilize time-domain measurements of a nonlinear device produce or extract a behavioral model from embeddings of these measurements. The method of producing a behavioral model comprises applying an input signal to the nonlinear device, sampling the input signal to produce input data, measuring a response of the device to produce output data, creating an embedded data set, fitting a function to the embedded data set, and verifying the fitted function. The apparatus comprises a signal generator that produces an input signal that is applied to the nonlinear device, the device producing an output signal in response. The apparatus further comprises a data acquisition system that samples and digitizes the input and output signals and a signal processing computer that produces an embedded data set from the digitized signals, fits a function to the embedded data set, and verifies the fitted function.

Abstract: A method utilizes time-domain measurements of a nonlinear device to produce or extract a behavioral model from embeddings of these measurements. The resulting behavioral model of the nonlinear device is a black-box model that accommodates nonlinear devices with one or more input ports and one or more output ports. The black-box model is a functional form that is a closed form function of input variables that produces an output as opposed to a structural form. The method of producing a behavioral model comprises the steps of applying an input signal to the nonlinear device, sampling the input signal to produce input data, measuring a response of the device to produce output data, creating an embedded data set, fitting a function to the embedded data set, and verifying the fitted function. The method may apply a CDMA type input signal in the step of applying, and/or may fit a novel radial basis function in the step of fitting a function. The input signal is constructed from a single CDMA signal representation.

Abstract: A system and a general method estimate figures of merit based on nonlinear modeling and nonlinear time series analysis. Terms in a nonlinear behavioral model that depend on nonlinear combinations of a fixed input signal value are precomputed, optimizing the behavioral model such that figures of merit are evaluated from a single short stimulus vector. The optimized nonlinear behavioral model can then be applied to evaluate figures of merit for multiple devices under test (DUTs) in a manufacturing line. A process continually verifies and adjusts the nonlinear behavioral model based on sub-sampling multiple DUTs in a manufacturing line and comparing their figures of merit based on nonlinear modeling with those based on conventional measurement procedures.