An Efficient Hardware Architecture for the Implementation of Multi-Step Look-Ahead Sigma-Delta Modulators

Basetas, Charis; Temenos, Nikos; Sotiriadis, Paul P.

doi:10.1109/iscas.2018.8351004

Cited by 3 publications

(2 citation statements)

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“…The SDM's maximum operating frequency f s corresponds to the register's one and, as expected, determines the input signal's maximum operating frequency f B that the architecture is able to process. Optionally, a dithering sequence can be employed to further decrease the SDM's output noise floor [32][33][34].…”

Section: Sdm Encodingmentioning

confidence: 99%

“…A well-known method to reduce the noise floor and improve the spectral characteristics of a quantized signal is to use sigma-delta modulators (SDMs) [32][33][34]. They convert a high-resolution signal (several bits) into a lower-bit one by employing the technique of oversampling; the input signal is sampled at a frequency much higher than the Nyquist, thus reducing the noise in the desired frequency band of interest.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Stochastic Computing FIR Filtering Using Sigma-Delta Modulated Signals

2022

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This work presents a soft-filtering digital signal processing architecture based on sigma-delta modulators and stochastic computing. A sigma-delta modulator converts the input high-resolution signal to a single-bit stream enabling filtering structures to be realized using stochastic computing’s negligible-area multipliers. Simulation in the spectral domain demonstrates the filter’s proper operation and its roll-off behavior, as well as the signal-to-noise ratio improvement using the sigma-delta modulator, compared to typical stochastic computing filter realizations. The proposed architecture’s hardware advantages are showcased with synthesis results for two FIR filters using FPGA and synopsys tools, while comparisons with standard stochastic computing-based hardware realizations, as well as with conventional binary ones, demonstrate its efficacy.

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Section: Sdm Encodingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%