Spectrum sensing for networked system using 1-bit compressed sensing with partial random circulant measurement matrices

Doohwan Lee, Tatsuya Sasaki, Takayuki Yamada, Kazunori Akabane, Yo Yamaguchi, Kazuhiro Uehara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Recently developed compressed sensing theory enables signal acquisition and reconstruction from incomplete information with high probability provided that the signal is sparsely represented in some basis. This paper applies compressed sensing for spectrum sensing in a networked system. To tackle the calculation and communication cost problems, this paper also applies structured compressed sensing and 1-bit compressed sensing. Measurement using the partial random circulant matrices can reduce the calculation cost at the sacrifice of a slightly increased number of measurements by utilizing the fact that a circulant matrix is decomposed by multiplications of structured matrices. This paper investigates the tradeoff between calculation cost and compression performance. 1-bit compressed sensing extracts only sign data (1-bit quantization) from measured data, and reconstructs the original signal from the extracted sign data. Therefore, 1-bit compressed sensing can save communication costs associated with spectrum sensing in a networked system. This paper evaluates the efficiency of 1-bit compressed sensing. In addition, this paper also proposes a block reconstruction algorithm for 1-bit compressed sensing that uses the block sparsity of the signals. Empirical study shows that partial random circulant matrices work as efficient as completely random measurement matrices for spectrum sensing and that 1-bit compressed sensing can be used for spectrum sensing with greatly reduced communication costs.

Original languageEnglish
Title of host publicationIEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Proceedings
DOIs
Publication statusPublished - 2012
Externally publishedYes
EventIEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Yokohama, Japan
Duration: May 6 2012Jun 9 2012

Other

OtherIEEE 75th Vehicular Technology Conference, VTC Spring 2012
CountryJapan
CityYokohama
Period5/6/126/9/12

Fingerprint

Compressed sensing
Spectrum Sensing
Compressed Sensing
Partial
Circulant Matrix
Communication Cost
Costs
Random Matrices
Communication
Signal theory
Quantization (signal)
Block Algorithm
Structured Matrices
Incomplete Information
Reconstruction Algorithm
Sparsity
Empirical Study
Quantization
Multiplication
Compression

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Applied Mathematics

Cite this

Lee, D., Sasaki, T., Yamada, T., Akabane, K., Yamaguchi, Y., & Uehara, K. (2012). Spectrum sensing for networked system using 1-bit compressed sensing with partial random circulant measurement matrices. In IEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Proceedings [6240259] https://doi.org/10.1109/VETECS.2012.6240259

Spectrum sensing for networked system using 1-bit compressed sensing with partial random circulant measurement matrices. / Lee, Doohwan; Sasaki, Tatsuya; Yamada, Takayuki; Akabane, Kazunori; Yamaguchi, Yo; Uehara, Kazuhiro.

IEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Proceedings. 2012. 6240259.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lee, D, Sasaki, T, Yamada, T, Akabane, K, Yamaguchi, Y & Uehara, K 2012, Spectrum sensing for networked system using 1-bit compressed sensing with partial random circulant measurement matrices. in IEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Proceedings., 6240259, IEEE 75th Vehicular Technology Conference, VTC Spring 2012, Yokohama, Japan, 5/6/12. https://doi.org/10.1109/VETECS.2012.6240259
Lee D, Sasaki T, Yamada T, Akabane K, Yamaguchi Y, Uehara K. Spectrum sensing for networked system using 1-bit compressed sensing with partial random circulant measurement matrices. In IEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Proceedings. 2012. 6240259 https://doi.org/10.1109/VETECS.2012.6240259
Lee, Doohwan ; Sasaki, Tatsuya ; Yamada, Takayuki ; Akabane, Kazunori ; Yamaguchi, Yo ; Uehara, Kazuhiro. / Spectrum sensing for networked system using 1-bit compressed sensing with partial random circulant measurement matrices. IEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Proceedings. 2012.
@inproceedings{918b6305a35846c0a99fb8ec9031babd,
title = "Spectrum sensing for networked system using 1-bit compressed sensing with partial random circulant measurement matrices",
abstract = "Recently developed compressed sensing theory enables signal acquisition and reconstruction from incomplete information with high probability provided that the signal is sparsely represented in some basis. This paper applies compressed sensing for spectrum sensing in a networked system. To tackle the calculation and communication cost problems, this paper also applies structured compressed sensing and 1-bit compressed sensing. Measurement using the partial random circulant matrices can reduce the calculation cost at the sacrifice of a slightly increased number of measurements by utilizing the fact that a circulant matrix is decomposed by multiplications of structured matrices. This paper investigates the tradeoff between calculation cost and compression performance. 1-bit compressed sensing extracts only sign data (1-bit quantization) from measured data, and reconstructs the original signal from the extracted sign data. Therefore, 1-bit compressed sensing can save communication costs associated with spectrum sensing in a networked system. This paper evaluates the efficiency of 1-bit compressed sensing. In addition, this paper also proposes a block reconstruction algorithm for 1-bit compressed sensing that uses the block sparsity of the signals. Empirical study shows that partial random circulant matrices work as efficient as completely random measurement matrices for spectrum sensing and that 1-bit compressed sensing can be used for spectrum sensing with greatly reduced communication costs.",
author = "Doohwan Lee and Tatsuya Sasaki and Takayuki Yamada and Kazunori Akabane and Yo Yamaguchi and Kazuhiro Uehara",
year = "2012",
doi = "10.1109/VETECS.2012.6240259",
language = "English",
isbn = "9781467309905",
booktitle = "IEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Proceedings",

}

TY - GEN

T1 - Spectrum sensing for networked system using 1-bit compressed sensing with partial random circulant measurement matrices

AU - Lee, Doohwan

AU - Sasaki, Tatsuya

AU - Yamada, Takayuki

AU - Akabane, Kazunori

AU - Yamaguchi, Yo

AU - Uehara, Kazuhiro

PY - 2012

Y1 - 2012

N2 - Recently developed compressed sensing theory enables signal acquisition and reconstruction from incomplete information with high probability provided that the signal is sparsely represented in some basis. This paper applies compressed sensing for spectrum sensing in a networked system. To tackle the calculation and communication cost problems, this paper also applies structured compressed sensing and 1-bit compressed sensing. Measurement using the partial random circulant matrices can reduce the calculation cost at the sacrifice of a slightly increased number of measurements by utilizing the fact that a circulant matrix is decomposed by multiplications of structured matrices. This paper investigates the tradeoff between calculation cost and compression performance. 1-bit compressed sensing extracts only sign data (1-bit quantization) from measured data, and reconstructs the original signal from the extracted sign data. Therefore, 1-bit compressed sensing can save communication costs associated with spectrum sensing in a networked system. This paper evaluates the efficiency of 1-bit compressed sensing. In addition, this paper also proposes a block reconstruction algorithm for 1-bit compressed sensing that uses the block sparsity of the signals. Empirical study shows that partial random circulant matrices work as efficient as completely random measurement matrices for spectrum sensing and that 1-bit compressed sensing can be used for spectrum sensing with greatly reduced communication costs.

AB - Recently developed compressed sensing theory enables signal acquisition and reconstruction from incomplete information with high probability provided that the signal is sparsely represented in some basis. This paper applies compressed sensing for spectrum sensing in a networked system. To tackle the calculation and communication cost problems, this paper also applies structured compressed sensing and 1-bit compressed sensing. Measurement using the partial random circulant matrices can reduce the calculation cost at the sacrifice of a slightly increased number of measurements by utilizing the fact that a circulant matrix is decomposed by multiplications of structured matrices. This paper investigates the tradeoff between calculation cost and compression performance. 1-bit compressed sensing extracts only sign data (1-bit quantization) from measured data, and reconstructs the original signal from the extracted sign data. Therefore, 1-bit compressed sensing can save communication costs associated with spectrum sensing in a networked system. This paper evaluates the efficiency of 1-bit compressed sensing. In addition, this paper also proposes a block reconstruction algorithm for 1-bit compressed sensing that uses the block sparsity of the signals. Empirical study shows that partial random circulant matrices work as efficient as completely random measurement matrices for spectrum sensing and that 1-bit compressed sensing can be used for spectrum sensing with greatly reduced communication costs.

UR - http://www.scopus.com/inward/record.url?scp=84865044448&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84865044448&partnerID=8YFLogxK

U2 - 10.1109/VETECS.2012.6240259

DO - 10.1109/VETECS.2012.6240259

M3 - Conference contribution

SN - 9781467309905

BT - IEEE 75th Vehicular Technology Conference, VTC Spring 2012 - Proceedings

ER -