Blind volterra system linearization with applications to post compensation of ADC nonlinearities

Shi, Kun; Redfern, A.J.

doi:10.1109/icassp.2012.6288690

Cited by 12 publications

(16 citation statements)

References 5 publications

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“…The employed correction system is shown in Fig. 1 [12]. The estimation part is located on the top of the figure and the correction part is located on its bottom.…”

Section: Studiedmentioning

confidence: 99%

“…Actually, if a frequency band at the input of the nonlinear system is free, distortions will appear in this band due to spectrum spreading. An algorithm will seek coefficients for the correction to restrict the output band to the original input band [10][11] [12]. This paper provides a system-level framework for the design of blind post-distortion techniques for band-limited signal, and the evaluation of their fundamental limits.…”

Section: Introductionmentioning

confidence: 99%

“…This paper provides a view on the limitations of these correction systems, and therefore provides an help for this design. Limitations are demonstrated using the algorithm presented in [12]. The aforementioned paper demonstrates the technique for a unique case with a white noise filtered signal of width 0.3 times the sampling frequency, noted f s , and an input SFDR of 60dB.…”

Section: Introductionmentioning

confidence: 99%

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Performance study of nonlinearities blind correction in wideband receivers

Vansebrouck

Jabbour

Desgreys

et al. 2014

2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS)

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International audienceThis paper studies a post-distortion correction technique applied to a nonlinear receiver. The employed technique relies on the assumption that the input signal is bandlimited and uses the signal spreading in the free energy band in order to perform the estimation. The study focuses on three points: the input distortion level impact, filter complexity and quantization. A good sizing of these key parameters is mandatory in order to have an optimized CMOS implementation

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“…The employed correction system is shown in Fig. 1 [12]. The estimation part is located on the top of the figure and the correction part is located on its bottom.…”

Section: Studiedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Performance study of nonlinearities blind correction in wideband receivers

Vansebrouck

Jabbour

Desgreys

et al. 2014

2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS)

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“…Motivated by the method in [9], we use a least-mean square (LMS) algorithm to blindly calibrate nonlinearity mismatch errors in two-channel TIADCs. In this paper, a certain degree of oversampling is assumed for the overall interleaved converter rather than for each individual converter.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, a certain degree of oversampling is assumed for the overall interleaved converter rather than for each individual converter. It means that by using the equivalent computational resource, this method can improve the bandwidth utilization twice compared to the method in [9]. Further, this method can save the amount of multiplications due to that it directly calibrates the mismatch errors rather than successively estimate and compensate.…”

mentioning

confidence: 99%

Blind calibration of nonlinearity mismatch errors in two-channel time-interleaved ADCs

Wang

Johansson

et al. 2014

2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS)

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To preserve the effective resolution of the individual converters in time-interleaved analog-to-digital converters (TIADCs), channel mismatches should be carefully corrected. In this paper, the proposed method is concentrated on achieving adaptive blind calibration for nonlinearity mismatches in twochannel TIADCs. It utilizes a least-mean square (LMS) algorithm as well as a polynomial-represented nonlinearity model. We assume a certain degree of oversampling for the overall converter to estimate and compensate for the mismatch errors. The calibration accuracy and convergence rate are investigated and evaluated through behavioral-level simulations. I. INTRODUCTIONTo satisfy the fast-growing requirement of sampling system, Black and Hodges proposed a sampling architecture which consists of multiple parallel converters operating in a circulatory manner, i.e., the time-interleaved ADCs (TIADCs) [1]. However the effective resolution of the sub-ADC is unfortunately not maintained in the overall sampling system due to mismatches between the parallel channels. During the last decades, much effort has been attracted on designing the correction methods for linear mismatches (e.g., DC-offset, gain, and time-skew mismatches) [2]- [5]. Whereas, only a few contributions have addressed the calibration method for nonlinearity mismatches [6]-[8], which can be easily introduced by the imperfection of the analog front-end circuits as well as the differential and integral nonlinearity (DNL and INL) of the sub-ADCs. In [6], a compensation method was proposed by using a randomization strategy, where the additional converters would increase the hardware cost. Training signals could be adopted to identify the mismatch errors for the post compensation [7], [8], which however would interrupt the normal operation and is incapable of tracking the mismatch variation.Motivated by the method in [9], we use a least-mean square (LMS) algorithm to blindly calibrate nonlinearity mismatch errors in two-channel TIADCs. In this paper, a certain degree of oversampling is assumed for the overall interleaved converter rather than for each individual converter. It means that by using the equivalent computational resource, this method can improve the bandwidth utilization twice compared to the method in [9]. Further, this method can save the amount of multiplications due to that it directly calibrates the mismatch errors rather than successively estimate and compensate.The outline of this paper is as follows. In Section II, we analyze the two-channel TIADC model with nonlinearity

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