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Design of Spectrum Processing Chiplet Based on FFT Algorithm

With the rapid development of electronic information and computer science, the fast Fourier transform (FFT) has played an increasingly important role in digital signal processing (DSP). This paper presented a spectrum processing chiplet design method to solve slow speed, low precision, and low resou...

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Detalles Bibliográficos
Autores principales: Meng, Baoping, Shan, Guangbao, Zheng, Yanwen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9964270/
https://www.ncbi.nlm.nih.gov/pubmed/36838102
http://dx.doi.org/10.3390/mi14020402
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author Meng, Baoping
Shan, Guangbao
Zheng, Yanwen
author_facet Meng, Baoping
Shan, Guangbao
Zheng, Yanwen
author_sort Meng, Baoping
collection PubMed
description With the rapid development of electronic information and computer science, the fast Fourier transform (FFT) has played an increasingly important role in digital signal processing (DSP). This paper presented a spectrum processing chiplet design method to solve slow speed, low precision, and low resource utilization in spectrum processing of general-purpose spectrum chips and field programmable gate array (FPGA). To realize signal processing, the Radix-2 4096-point FFT algorithm with pipeline structure is used to process spectral signals extracted from the time domain. To reduce the harm caused by spectrum leakage, a windowing module is added to optimize the input data, and the clock gating unit (CGU) is used to perform low-power management on the entire clock reset. The result shows the chiplet takes 0.368 ms to complete a 4096-point frequency sweep under a clock frequency of 61.44 MHz. The chiplet significantly improves speed and accuracy in spectrum processing, which has great application potential in wireless communication.
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spelling pubmed-99642702023-02-26 Design of Spectrum Processing Chiplet Based on FFT Algorithm Meng, Baoping Shan, Guangbao Zheng, Yanwen Micromachines (Basel) Article With the rapid development of electronic information and computer science, the fast Fourier transform (FFT) has played an increasingly important role in digital signal processing (DSP). This paper presented a spectrum processing chiplet design method to solve slow speed, low precision, and low resource utilization in spectrum processing of general-purpose spectrum chips and field programmable gate array (FPGA). To realize signal processing, the Radix-2 4096-point FFT algorithm with pipeline structure is used to process spectral signals extracted from the time domain. To reduce the harm caused by spectrum leakage, a windowing module is added to optimize the input data, and the clock gating unit (CGU) is used to perform low-power management on the entire clock reset. The result shows the chiplet takes 0.368 ms to complete a 4096-point frequency sweep under a clock frequency of 61.44 MHz. The chiplet significantly improves speed and accuracy in spectrum processing, which has great application potential in wireless communication. MDPI 2023-02-07 /pmc/articles/PMC9964270/ /pubmed/36838102 http://dx.doi.org/10.3390/mi14020402 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Meng, Baoping
Shan, Guangbao
Zheng, Yanwen
Design of Spectrum Processing Chiplet Based on FFT Algorithm
title Design of Spectrum Processing Chiplet Based on FFT Algorithm
title_full Design of Spectrum Processing Chiplet Based on FFT Algorithm
title_fullStr Design of Spectrum Processing Chiplet Based on FFT Algorithm
title_full_unstemmed Design of Spectrum Processing Chiplet Based on FFT Algorithm
title_short Design of Spectrum Processing Chiplet Based on FFT Algorithm
title_sort design of spectrum processing chiplet based on fft algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9964270/
https://www.ncbi.nlm.nih.gov/pubmed/36838102
http://dx.doi.org/10.3390/mi14020402
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