Analysis, Blind Identification, and Correction of Frequency Response Mismatch in Two-Channel Time-Interleaved ADCs

Wang

et al. 2019

Applied Sciences

Time-interleaved analog-to-digital converter (TIADC) is a good option for high sampling rate applications. However, the inevitable sample-and-hold (S/H) mismatches between channels incur undesirable error and then affect the TIADC’s dynamic performance. Several calibration methods have been proposed for S/H mismatches which either need training signals or have less extensive applicability for different input signals and different numbers of channels. This paper proposes a statistics-based calibration algorithm for S/H mismatches in M-channel TIADCs. Initially, the mismatch coefficients are identified by eliminating the statistical differences between channels. Subsequently, the mismatch-induced error is approximated by employing variable multipliers and differentiators in several Richardson iterations. Finally, the error is subtracted from the original output signal to approximate the expected signal. Simulation results illustrate the effectiveness of the proposed method, the selection of key parameters and the advantage to other methods.

Section: Introductionmentioning

confidence: 99%

Calibration for Sample-And-Hold Mismatches in M-Channel TIADCs Based on Statistics

Wang

et al. 2019

Applied Sciences

“…However, it only works well for 2-TIADCs. Complex signal processing is employed in methods proposed in [11,12,13,14] to estimate the mismatch coefficients and suppress spurious components. This paper proposes a training signal based calibration method for FRMs in M-TIADCs.…”

Section: Introductionmentioning

confidence: 99%

A calibration method for frequency response mismatches in <i>M</i>-channel time-interleaved analog-to-digital converters

IEICE Electron. Express

2016

Frequency response mismatches (FRMs) in time-interleaved analog-to-digital converters (TIADCs) generate undesired spurs degrading the performance of TIADCs. This paper introduces a digital calibration method for the FRM in M-channel TIADCs (M-TIADCs). This method exploits fixed differentiator finite-impulse response (FIR) filters and the Hadamard transform to reconstruct the mismatch induced error signal. The mismatch parameters are estimated utilizing a short training signal and the least square (LS) method. Our method is simpler in terms of implementation compared with conventional methods as cumbersome time-varying filters, complex signal processing and front-end hardware modifications are avoided. Numerical simulation results demonstrate the efficacy and efficiency of the proposed method. Keywords: frequency response, time-interleaved ADC, mismatch, polynomial representation, Hadamard transform, least square Classification: Circuits and modules for electronic instrumentation

“…Most of them aim at the compensation methods for the linear mismatches, including gain, time-skew and frequency response mismatches [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. By comparison, relatively few papers have been published to address the nonlinear mismatches problem, which stems from the imperfection of front-end circuits, as well as the differential and integral nonlinearities of sub-ADCs [21][22][23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

A Calibration Method for Nonlinear Mismatches in M-Channel Time-Interleaved Analog-to-Digital Converters Based on Hadamard Sequences

Wang

et al. 2016

Applied Sciences

Abstract:The time-interleaved analog-to-digital converter (TIADC) is an architecture used to achieve a high sampling rate and high dynamic performance. However, estimation and compensation methods are required to maintain the dynamic performance of the constituent analog-to-digital converters (ADCs) due to channel mismatches. This paper proposes a blind adaptive method to calibrate the nonlinear mismatches in M-channel TIADCs (M-TIADCs). The nonlinearity-induced error signal is reconstructed by the proposed multiplier Hadamard transform (MHT) structure, and the nonlinear parameters are estimated by the filtered-X least-mean square (FxLMS) algorithm. The performance of cascade calibration is also analyzed. The numerical simulation results show that the proposed method consumes much less hardware resources while maintaining the calibration performance.