### Abstract

Applications like spectrum sensing, radar signal processing, and pattern matching by convolving a signal with a long code, as in GPS, require large FFT sizes. ASIC implementations of such FFTs are challenging due to their large silicon area and high power consumption. However, the signals in these applications are sparse, i.e., the energy at the output of the FFT/IFFT is concentrated at a limited number of frequencies and with zero/negligible energy at most frequencies. Recent advances in signal processing have shown that, for such sparse signals, a new algorithm called the sparse FFT (sFFT) can compute the Fourier transform more efficiently than traditional FFTs [1].

Original language | English (US) |
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Title of host publication | 2014 IEEE International Solid-State Circuits Conference, ISSCC 2014 - Digest of Technical Papers |

Publisher | Institute of Electrical and Electronics Engineers Inc. |

Pages | 458-459 |

Number of pages | 2 |

ISBN (Print) | 9781479909186 |

DOIs | |

State | Published - Jan 1 2014 |

Event | 2014 61st IEEE International Solid-State Circuits Conference, ISSCC 2014 - San Francisco, CA, United States Duration: Feb 9 2014 → Feb 13 2014 |

### Publication series

Name | Digest of Technical Papers - IEEE International Solid-State Circuits Conference |
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Volume | 57 |

ISSN (Print) | 0193-6530 |

### Other

Other | 2014 61st IEEE International Solid-State Circuits Conference, ISSCC 2014 |
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Country | United States |

City | San Francisco, CA |

Period | 2/9/14 → 2/13/14 |

### Fingerprint

### ASJC Scopus subject areas

- Electronic, Optical and Magnetic Materials
- Electrical and Electronic Engineering

### Cite this

*2014 IEEE International Solid-State Circuits Conference, ISSCC 2014 - Digest of Technical Papers*(pp. 458-459). [6757512] (Digest of Technical Papers - IEEE International Solid-State Circuits Conference; Vol. 57). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSCC.2014.6757512

**A 0.75-million-point fourier-transform chip for frequency-sparse signals.** / Abari, Omid; Hamed, Ezz; Hassanieh, Haitham; Agarwal, Abhinav; Katabi, Dina; Chandrakasan, Anantha P.; Stojanovic, Vladimir.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*2014 IEEE International Solid-State Circuits Conference, ISSCC 2014 - Digest of Technical Papers.*, 6757512, Digest of Technical Papers - IEEE International Solid-State Circuits Conference, vol. 57, Institute of Electrical and Electronics Engineers Inc., pp. 458-459, 2014 61st IEEE International Solid-State Circuits Conference, ISSCC 2014, San Francisco, CA, United States, 2/9/14. https://doi.org/10.1109/ISSCC.2014.6757512

}

TY - GEN

T1 - A 0.75-million-point fourier-transform chip for frequency-sparse signals

AU - Abari, Omid

AU - Hamed, Ezz

AU - Hassanieh, Haitham

AU - Agarwal, Abhinav

AU - Katabi, Dina

AU - Chandrakasan, Anantha P.

AU - Stojanovic, Vladimir

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Applications like spectrum sensing, radar signal processing, and pattern matching by convolving a signal with a long code, as in GPS, require large FFT sizes. ASIC implementations of such FFTs are challenging due to their large silicon area and high power consumption. However, the signals in these applications are sparse, i.e., the energy at the output of the FFT/IFFT is concentrated at a limited number of frequencies and with zero/negligible energy at most frequencies. Recent advances in signal processing have shown that, for such sparse signals, a new algorithm called the sparse FFT (sFFT) can compute the Fourier transform more efficiently than traditional FFTs [1].

AB - Applications like spectrum sensing, radar signal processing, and pattern matching by convolving a signal with a long code, as in GPS, require large FFT sizes. ASIC implementations of such FFTs are challenging due to their large silicon area and high power consumption. However, the signals in these applications are sparse, i.e., the energy at the output of the FFT/IFFT is concentrated at a limited number of frequencies and with zero/negligible energy at most frequencies. Recent advances in signal processing have shown that, for such sparse signals, a new algorithm called the sparse FFT (sFFT) can compute the Fourier transform more efficiently than traditional FFTs [1].

UR - http://www.scopus.com/inward/record.url?scp=84898074091&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84898074091&partnerID=8YFLogxK

U2 - 10.1109/ISSCC.2014.6757512

DO - 10.1109/ISSCC.2014.6757512

M3 - Conference contribution

AN - SCOPUS:84898074091

SN - 9781479909186

T3 - Digest of Technical Papers - IEEE International Solid-State Circuits Conference

SP - 458

EP - 459

BT - 2014 IEEE International Solid-State Circuits Conference, ISSCC 2014 - Digest of Technical Papers

PB - Institute of Electrical and Electronics Engineers Inc.

ER -