An estimation method of timing mismatch error in hybrid filter bank DACs

Yin, Lin; Tian, Shulin; Liu, Ke; Guo, Guangkun; Xiao, Yegui

doi:10.1587/elex.17.20200126

Cited by 3 publications

(1 citation statement)

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“…1 which depicts an architecture of a M-channel BI-DAC, the bandwidth of the BI-DAC output ( ) can be increased M times as each sub-DAC's output bandwidth. However, there exist different errors such as time delay error caused by the length difference between different sub-channels [13], phase offset caused by the local oscillator signal nonzero initial phase [14], and the aliasing errors due to the non-ideality of analog mixers and filters [15,16,17,18], which can cause ( ) to be deteriorated. To cancel these errors, various methods have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Noniterative WLS design of digital FIR filters for aliasing errors cancellation in bandwidth interleaving digital-to-analog converter

Yang

Liu

Zhang

et al. 2022

IEICE Electron. Express

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This paper presented a noniterative weighted least squares (WLS) design of digital finite impulse response (FIR) filters for canceling the aliasing errors caused by the non-ideality of analog mixers and filters in bandwidth interleaving digital-to-analog converter (BI-DAC). Taking a BI-DAC with M sub-DACs as an example, we firstly deduced the approximation error function. Then, based on this approximation error function, the optimum coefficients of all digital FIR filters were obtained by using the noniterative WLS method. Further, we deduced the computational complexity of our presented noniterative WLS design.Several design examples were given to verify the performance of our presented noniterative WLS design containing their effectiveness and computational. The simulation results showed that, by using our presented noniterative WLS design, the minimum distortion error was 0.021dB, and the maximum aliasing error was -67dB which satisfied the desired spurious free dynamic range (SFDR) in a 11-bit BI-DAC system. Finally, we compared the computational complexity among our presented noniterative WLS design and another three optimal designs, and satisfactory simulation results were obtained.

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Section: Introductionmentioning

confidence: 99%

Noniterative WLS design of digital FIR filters for aliasing errors cancellation in bandwidth interleaving digital-to-analog converter

Yang

Liu

Zhang

et al. 2022

IEICE Electron. Express

Self Cite

View full text Add to dashboard Cite

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Optimal design of digital FIR filters based on back propagation neural network

Yang

et al. 2023

IEICE Electron. Express

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In the traditional digital finite impulse response (FIR) filter design, there exist some limitations. For instance, unwanted signals cannot be filtered out by using these FIR filters. Therefore, to break these limitations, this paper proposes an optimization method for designing digital FIR filters based on the back propagation neural network (BPNN) algorithm. Firstly, an amplitude response model has been established based on the linear properties of the digital FIR filters. Then, the BPNN algorithm has been used to minimize the estimation error between the ideal and the actual amplitude response such that the optimal coefficients of the digital FIR filter can be obtained. Finally, several design examples are used to verify the performance of our proposed optimal design based on BPNN. The simulation results show that, compared with the optimal designs based on the sequential and rectangular window, our proposed optimal design based on BPNN can achieve better filtering effectiveness but at the cost of larger computational complexity.

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