On-the-fly Computation Method in Field-Programmable Gate Array for Analog-to-Digital Converter Linearity Testing

This paper presents a new approach to linearity testing of analog-to-digital converters (ADCs) through on-the-fly computation in field-programmable gate array (FPGA) hardware. The proposed method computes the linearity while it is processing without compromising the accuracy of the measurement, so very little overhead time is required to compute the final linearity. The results will be displayed immediately after a single ramp is supplied to the device under test. This is a cost-effective chip testing solution for semiconductor companies, achieved by reducing computing time and utilization of low-cost and low-specification automatic test equipment (ATE). The experimental results showed that the on-the-fly computation method significantly reduced the computation time (up to 44.4%) compared to the conventional process. Thus, for every 100M 12-bit ADC tested with 32 hits per code, the company can save up to 139,972 Php on electricity consumption

On-the-fly computation method in field-programmable gate array for analog-to-digital converter linearity testing

© 2018 Published by ITB Journal Publisher. This paper presents a new approach to linearity testing of analog-to-digital converters (ADCs) through on-the-fly computation in field-programmable gate array (FPGA) hardware. The proposed method computes the linearity while it is processing without compromising the accuracy of the measurement, so very little overhead time is required to compute the final linearity. The results will be displayed immediately after a single ramp is supplied to the device under test. This is a cost-effective chip testing solution for semiconductor companies, achieved by reducing computing time and utilization of low-cost and low-specification automatic test equipment (ATE). The experimental results showed that the on-the-fly computation method significantly reduced the computation time (up to 44.4%) compared to the conventional process. Thus, for every 100M 12-bit ADC tested with 32 hits per code, the company can save up to 139,972 Php on electricity consumption

Test Strategies for Embedded ADC Cores in a System-on-Chip, A Case Study

Testing of a deeply embedded mixed-signal core in a System-on-Chip (SoC) is a challenging issue due to the communication bottleneck in accessing the core from external automatic test equipment. Consequently, in many cases the preferred approach is built-in self-test (BIST), where the major part of test activity is performed within the unit-under-test and only final results are communicated to the external tester. IEEE Standard 1500 provides efficient test infrastructure for testing digital cores; however, its applications in mixed-signal core test remain an open issue. In this paper we address the problem of implementing BIST of a mixed-signal core in a IEEE Std 1500 test wrapper and discuss advantages and drawbacks of different test strategies. While the case study is focused on histogram based test of ADC, test strategies of other types of mixed-signal cores related to trade-off between performance (i.e., test time) and required resources are likely to follow similar conclusions

Programmable CMOS Analog-to-Digital Converter Design and Testability

In this work, a programmable second order oversampling CMOS delta-sigma analog-to-digital converter (ADC) design in 0.5µm n-well CMOS processes is presented for integration in sensor nodes for wireless sensor networks. The digital cascaded integrator comb (CIC) decimation filter is designed to operate at three different oversampling ratios of 16, 32 and 64 to give three different resolutions of 9, 12 and 14 bits, respectively which impact the power consumption of the sensor nodes. Since the major part of power consumed in the CIC decimator is by the integrators, an alternate design is introduced by inserting coder circuits and reusing the same integrators for different resolutions and oversampling ratios to reduce power consumption. The measured peak signal-to-noise ratio (SNR) for the designed second order delta-sigma modulator is 75.6dB at an oversampling ratio of 64, 62.3dB at an oversampling ratio of 32 and 45.3dB at an oversampling ratio of 16. The implementation of a built-in current sensor (BICS) which takes into account the increased background current of defect-free circuits and the effects of process variation on ΔIDDQ testing of CMOS data converters is also presented. The BICS uses frequency as the output for fault detection in CUT. A fault is detected when the output frequency deviates more than ±10% from the reference frequency. The output frequencies of the BICS for various model parameters are simulated to check for the effect of process variation on the frequency deviation. A design for on-chip testability of CMOS ADC by linear ramp histogram technique using synchronous counter as register in code detection unit (CDU) is also presented. A brief overview of the histogram technique, the formulae used to calculate the ADC parameters, the design implemented in 0.5µm n-well CMOS process, the results and effectiveness of the design are described. Registers in this design are replaced by 6T-SRAM cells and a hardware optimized on-chip testability of CMOS ADC by linear ramp histogram technique using 6T-SRAM as register in CDU is presented. The on-chip linear ramp histogram technique can be seamlessly combined with ΔIDDQ technique for improved testability, increased fault coverage and reliable operation

Built-in self-test and self-calibration for analog and mixed signal circuits

Analog-to-digital converters (ADC) are one of the most important components in modern electronic systems. In the mission-critical applications such as automotive, the reliability of the ADC is critical as the ADC impacts the system level performance. Due to the aging effect and environmental changes, the performance of the ADC may degrade and even fail to meet the accuracy requirement over time. Built-in self-test (BIST) and self-calibration are becoming the ultimate solution to achieve lifetime reliability. This dissertation introduces two ADC testing algorithms and two ADC built-in self-test circuit implementations to test the ADC integral nonlinearity (INL) and differential nonlinearity (DNL) on-chip. In the first testing algorithm, the ultrafast stimulus error removal and segmented model identification of linearity errors (USER-SMILE) is developed for ADC built-in self-test, which eliminates the need for precision stimulus and reduces the overall test time. In this algorithm, the ADC is tested twice with a nonlinear ramp, instead of using a linear ramp signal. Therefore, the stimulus can be easily generated on-chip in a low-cost way. For the two ramps, there is a constant voltage shift in between. As the input stimulus linearity is completely relaxed, there is no requirement on the waveform of the input stimulus as long as it covers the ADC input range. In the meantime, the high-resolution ADC linearity is modeled with segmented parameters, which reduces the number of samples required for achieving high-precision test, thus saving the test time. As a result, the USER-SMILE algorithm is able to use less than 1 sample/code nonlinear stimulus to test high resolution ADCs with less than 0.5 least significant bit (LSB) INL estimation error, achieving more than 10-time test time reduction. This algorithm is validated with both board-level implementation and on-chip silicon implementation. The second testing algorithm is proposed to test the INL/DNL for multi-bit-per-stages pipelined ADCs with reduced test time and better test coverage. Due to the redundancy characteristics of multi-bit-per-stages pipelined ADC, the conventional histogram test cannot estimate and calibrate the static linearity accurately. The proposed method models the pipelined ADC nonlinearity as segmented parameters with inter-stage gain errors using the raw codes instead of the final output codes. During the test phase, a pure sine wave is sent to the ADC as the input and the model parameters are estimated from the output data with the system identification method. The modeled errors are then removed from the digital output codes during the calibration phase. A high-speed 12-bit pipelined ADC is tested and calibrated with the proposed method. With only 4000 samples, the 12-bit ADC is accurately tested and calibrated to achieve less than 1 LSB INL. The ADC effective number of bits (ENOB) is improved from 9.7 bits to 10.84 bits and the spurious-free dynamic range (SFDR) is improved by more than 20dB after calibration. In the first circuit implementation, a low-cost on-chip built-in self-test solution is developed using an R2R digital-to-analog converter (DAC) structure as the signal generator and the voltage shift generator for ADC linearity test. The proposed DAC is a subradix-2 R2R DAC with a constant voltage shift generation capability. The subradix-2 architecture avoids positive voltage gaps caused by mismatches, which relaxes the DAC matching requirements and reduces the design area. The R2R DAC based BIST circuit is fabricated in TSMC 40nm technology with a small area of 0.02mm^2. Measurement results show that the BIST circuit is capable of testing a 15-bit ADC INL accurately with less than 0.5 LSB INL estimation error. In the second circuit implementation, a complete SAR ADC built-in self-test solution using the USER-SMILE is developed and implemented in a 28nm automotive microcontroller. A low-cost 12-bit resistive DAC with less than 12-bit linearity is used as the signal generator to test and calibrate a SAR ADC with a target linearity of 12 bits. The voltage shift generation is created inside the ADC with capacitor switching. The entire algorithm processing unit for USER-SMILE algorithm is also implemented on chip. The final testing results are saved in the memory for further digital calibration. Both the total harmonic distortion (THD) and the SFDR are improved by 20dB after calibration, achieving -84.5dB and 86.5dB respectively. More than 700 parts are tested to verify the robustness of the BIST solution