Digital Blind Background Calibration of Imperfections in Time-Interleaved ADCs

Mafi, Hamidreza; Yargholi, Mostafa; Yavari, Mohammad

doi:10.1109/tcsi.2017.2647758

Cited by 36 publications

(20 citation statements)

References 23 publications

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“…The signal-to-noise-and-distortion (SINAD) is 62.15 dB and the LSSR is 59.07 dBc before calibration, while they are enhanced to 74.95 dB and 77.53 dBc after Stage 1 calibration, and then to 75.78 dB and 91.39 dBc after Stage 2 calibration. The identified coefficients in Stage 2 calibration plotted in Figure 9 and those in Table 2 are close but not identical, because we use y[n] and z[n] to approximate the error rather thanỹ[n] in (8) and (9). Therefore, the algorithm proposed in this paper can accurately identify the mismatch coefficients without much prior information of the input signal other than its WSS and modulo 8 quasi-stationary properties.…”

Section: Effectivenessmentioning

confidence: 98%

“…In reality, electronic mismatches, which periodically modulate the input signal and degrade the output signal's dynamic performance, are inevitable. In recent years, methods have been put forward to mitigate timing mismatches [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17], bandwidth mismatches [18,19], frequency response mismatches [20][21][22][23][24][25][26][27][28][29][30] (frequency response mismatch contains the gain, timing and bandwidth mismatches altogether), and nonlinearity mismatches [31][32][33][34]. To consider all kinds of mismatches, ref.…”

Section: Introductionmentioning

confidence: 99%

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

Liu

Wang

et al. 2019

Applied Sciences

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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.

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Section: Effectivenessmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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

Liu

Wang

et al. 2019

Applied Sciences

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“…Unfortunately, TIADC performance suffers from channel mismatches including offset, gain and timing mismatch due to process, voltage and temperature variations. These mismatches will significantly decrease SNR and SFDR of TIADC [9,10,11,12,13,14]. In particular, the timing mismatch plays the most critical role for it is becoming severer with the increasing input frequency and overshadow the effect of other mismatches for broadband input [15,16,17].…”

Section: Introductionmentioning

confidence: 99%

Calibration of timing mismatch in TIADC based on monotonicity detecting of sampled data

Yin

Sun

Chen

et al. 2020

IEICE Electron. Express

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In this paper, a calibration method aiming at the timing mismatch existing in the TIADC (Time-Interleaved Analog-to-Digital Converter) is proposed. Monotonicity detecting of the sampled data is employed to estimate the mismatch error, in which only additive operation is involved. Besides that, an improved Taylor expansion method is used to compensate the mismatch error. The processes of the estimation and the compensation are designed to constitute an adaptive loop, so that the calibration can be run in real-time. Compared with other approaches, this method consumes less hardware resources and has a good calibration result.

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“…TIADC technology improves sampling rate, but channel mismatches are brought in. In TIADC systems, channel mismatches seriously degrade the signalto-noise and distortion ratio (SNDR) and spurious-free dynamic range (SFDR) [18,19,20,21,22,23,24,25,26,27,28,29]. In published literature, studies of TIADC are based on the effects of channel mismatches on the spectrum or dynamic performance such as SNDR and SFDR [14,16,17,18,19,20,21,22,23,24,25,26,27,29,30,31,32].…”

Section: Introductionmentioning

confidence: 99%

Analysis of TIADC channel mismatch effects on high-resolution range profile

Xiao

Zhang

2020

IEICE Electron. Express

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The wideband echo signals of the imaging radar can be processed by pulse compression to obtain high-resolution range profile (HRRP). The resolution of HRRP is proportional to the signal bandwidth. The pursuit of high resolution makes the bandwidth of radar transmitting signal larger and larger. And the corresponding sampling rate of receiver becomes so high that analog-to-digital conversion cannot be realized by a single chip correctly. Time-interleaved analog-to-digital converter (TIADC) technique increases sampling rate of radar receiver, but channel mismatches are brought in. Channel mismatches significantly deteriorate the dynamic performance of radar receiver. Effects of channel mismatch on SNR, SNDR and SFDR are studied in previous literatures. Derivation and simulation of TIADC channel mismatch effecting on HRRP are performed in this letter. Simulation results show that without considering the amplitude-frequency distortion and phase-frequency distortions of the radar system, when the gain mismatch is less than 0.7 times and the clock mismatch is less than 0.25 rad, the influence of the channel mismatch on the HRRP can be neglected. The results provide a reference for system design and compensation method, which are useful for the designer to determine whether complex channel mismatch calibration is necessary under specific application background.

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Digital Blind Background Calibration of Imperfections in Time-Interleaved ADCs

Cited by 36 publications

References 23 publications

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

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

Calibration of timing mismatch in TIADC based on monotonicity detecting of sampled data

Analysis of TIADC channel mismatch effects on high-resolution range profile

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