Spin-Torque Based Radio-Frequency Signal Classification Front-End

Yasser Rezaeiyan; Milad Zamani; Sonal Shreya; Hooman Farkhani; Farshad Moradi

doi:10.1109/ISCAS46773.2023.10181428

Spin-Torque Based Radio-Frequency Signal Classification Front-End

Yasser Rezaeiyan, Milad Zamani, Sonal Shreya, Hooman Farkhani, Farshad Moradi

Department of Electrical and Computer Engineering - Electronics and Photonics

Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review

2 Citations (Scopus)

Abstract

Many classification applications rely on real-time processing and detection of RF signals at high frequencies. RF signal sampling requires sophisticated hardware, i.e., broadband analog front-ends and high-speed analog-to-digital converters according to the well-known Shannon-Nyquist theorem. Such devices either are expensive or suffer from limited detection bandwidths and sampling rates. Here, we proposed a novel spintronic-based classification front-end for real-time analysis and classification of RF signals. In comparison to the conventional CMOS-based systems, the proposed system can increase the classification speed dramatically while consuming an order of magnitude less power.

Original language	English
Title of host publication	2023 IEEE International Symposium on Circuits and Systems (ISCAS)
Publisher	IEEE
Publication date	Jul 2023
ISBN (Electronic)	978-1-6654-5109-3, 978-1-6654-5110-9
DOIs	https://doi.org/10.1109/ISCAS46773.2023.10181428
Publication status	Published - Jul 2023
Event	The IEEE International Symposium on Circuits and Systems (ISCAS) - Duration: 21 May 2023 → 25 May 2023

Conference

Conference	The IEEE International Symposium on Circuits and Systems (ISCAS)
Period	21/05/2023 → 25/05/2023

Series	IEEE International Symposium on Circuits and Systems proceedings
ISSN	2158-1525

Keywords

Low noise amplifier
noise
spin-torque diode effect
spintronic
vortex nano-oscillators

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10.1109/ISCAS46773.2023.10181428

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title = "Spin-Torque Based Radio-Frequency Signal Classification Front-End",

abstract = "Many classification applications rely on real-time processing and detection of RF signals at high frequencies. RF signal sampling requires sophisticated hardware, i.e., broadband analog front-ends and high-speed analog-to-digital converters according to the well-known Shannon-Nyquist theorem. Such devices either are expensive or suffer from limited detection bandwidths and sampling rates. Here, we proposed a novel spintronic-based classification front-end for real-time analysis and classification of RF signals. In comparison to the conventional CMOS-based systems, the proposed system can increase the classification speed dramatically while consuming an order of magnitude less power.",

keywords = "Low noise amplifier, noise, spin-torque diode effect, spintronic, vortex nano-oscillators",

author = "Yasser Rezaeiyan and Milad Zamani and Sonal Shreya and Hooman Farkhani and Farshad Moradi",

year = "2023",

month = jul,

doi = "10.1109/ISCAS46773.2023.10181428",

language = "English",

series = "IEEE International Symposium on Circuits and Systems proceedings",

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note = "The IEEE International Symposium on Circuits and Systems (ISCAS) ; Conference date: 21-05-2023 Through 25-05-2023",

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Rezaeiyan, Y , Zamani, M , Shreya, S , Farkhani, H & Moradi, F 2023, Spin-Torque Based Radio-Frequency Signal Classification Front-End. in 2023 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, IEEE International Symposium on Circuits and Systems proceedings, The IEEE International Symposium on Circuits and Systems (ISCAS), 21/05/2023. https://doi.org/10.1109/ISCAS46773.2023.10181428

Spin-Torque Based Radio-Frequency Signal Classification Front-End. / Rezaeiyan, Yasser ; Zamani, Milad ; Shreya, Sonal et al.
2023 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2023. (IEEE International Symposium on Circuits and Systems proceedings).

Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Spin-Torque Based Radio-Frequency Signal Classification Front-End

AU - Rezaeiyan, Yasser

AU - Zamani, Milad

AU - Shreya, Sonal

AU - Farkhani, Hooman

AU - Moradi, Farshad

PY - 2023/7

Y1 - 2023/7

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AB - Many classification applications rely on real-time processing and detection of RF signals at high frequencies. RF signal sampling requires sophisticated hardware, i.e., broadband analog front-ends and high-speed analog-to-digital converters according to the well-known Shannon-Nyquist theorem. Such devices either are expensive or suffer from limited detection bandwidths and sampling rates. Here, we proposed a novel spintronic-based classification front-end for real-time analysis and classification of RF signals. In comparison to the conventional CMOS-based systems, the proposed system can increase the classification speed dramatically while consuming an order of magnitude less power.

KW - Low noise amplifier

KW - noise

KW - spin-torque diode effect

KW - spintronic

KW - vortex nano-oscillators

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DO - 10.1109/ISCAS46773.2023.10181428

M3 - Article in proceedings

T3 - IEEE International Symposium on Circuits and Systems proceedings

BT - 2023 IEEE International Symposium on Circuits and Systems (ISCAS)

PB - IEEE

T2 - The IEEE International Symposium on Circuits and Systems (ISCAS)

Y2 - 21 May 2023 through 25 May 2023

ER -

Spin-Torque Based Radio-Frequency Signal Classification Front-End

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Keywords

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