메뉴 건너뛰기




Volumn 11, Issue 6, 2012, Pages 2116-2125

Sparsity order estimation and its application in compressive spectrum sensing for cognitive radios

Author keywords

cognitive radio; compressive sampling; curve fitting; Sparsity order estimation; wideband spectrum sensing

Indexed keywords

ACQUISITION COSTS; CLOSED FORM; COMPRESSIVE SAMPLING; DATA FITTINGS; HIGH-DIMENSIONAL; NUMBER OF SAMPLES; ORDER ESTIMATION; SAMPLING RATES; SENSING PERFORMANCE; SIGNAL DIMENSIONS; SIGNALS OF INTERESTS; SPARSE SIGNALS; SPECTRUM SENSING; STATISTICAL LEARNING; UPPER BOUND; WIDE SPECTRUM; WIDE-BAND; WIDEBAND SPECTRUM;

EID: 84863002432     PISSN: 15361276     EISSN: None     Source Type: Journal    
DOI: 10.1109/TWC.2012.050112.110505     Document Type: Article
Times cited : (141)

References (25)
  • 1
    • 85032750937 scopus 로고    scopus 로고
    • An introduction to compressive sampling
    • Mar.
    • E. J. Candes and M. B. Wakin, "An introduction to compressive sampling," IEEE Signal Process. Mag., vol. 25, no. 2, pp. 21-30, Mar. 2008.
    • (2008) IEEE Signal Process. Mag. , vol.25 , Issue.2 , pp. 21-30
    • Candes, E.J.1    Wakin, M.B.2
  • 2
    • 33645712892 scopus 로고    scopus 로고
    • Compressed sensing
    • Apr.
    • D. L. Donoho, "Compressed sensing," IEEE Trans. Inf. Theory, vol. 52, no. 4, pp. 1289-1306, Apr. 2006.
    • (2006) IEEE Trans. Inf. Theory , vol.52 , Issue.4 , pp. 1289-1306
    • Donoho, D.L.1
  • 3
    • 55649115527 scopus 로고    scopus 로고
    • A simple proof of the restricted isometry property for random matrices
    • Dec.
    • R. Baraniuk, M. Davenport, R. DeVore, and M. Wakin, "A simple proof of the restricted isometry property for random matrices," Const. Approx., vol. 28, no. 3, pp. 253-263, Dec. 2008.
    • (2008) Const. Approx. , vol.28 , Issue.3 , pp. 253-263
    • Baraniuk, R.1    Davenport, M.2    Devore, R.3    Wakin, M.4
  • 5
    • 70349223782 scopus 로고    scopus 로고
    • RLS-weighted lasso for adaptive estimation of sparse signals
    • D. Angelosante and G. B. Giannakis, "RLS-weighted lasso for adaptive estimation of sparse signals," in Proc. 2009 IEEE ICASSP Conf., pp. 3245-3248.
    • Proc. 2009 IEEE ICASSP Conf. , pp. 3245-3248
    • Angelosante, D.1    Giannakis, G.B.2
  • 6
    • 73849097267 scopus 로고    scopus 로고
    • Information-Theoretic limits on sparsity recovery in the high-dimensional and noisy setting
    • Dec.
    • M. J. Wainwright, "Information-Theoretic limits on sparsity recovery in the high-dimensional and noisy setting," IEEE Trans. Inf. Theory, vol. 55, no. 12, pp. 5728-5741, Dec. 2009.
    • (2009) IEEE Trans. Inf. Theory , vol.55 , Issue.12 , pp. 5728-5741
    • Wainwright, M.J.1
  • 7
    • 77956932923 scopus 로고    scopus 로고
    • Informationtheoretic limits on sparse support recovery: Dense versus sparse measurement
    • June
    • W. Wang, M. J. Wainwright, and K. Ramchandran, "Informationtheoretic limits on sparse support recovery: Dense versus sparse measurement," IEEE Trans. Inf. Theory, vol. 56, no. 6, pp. 2967-2979, June 2010.
    • (2010) IEEE Trans. Inf. Theory , vol.56 , Issue.6 , pp. 2967-2979
    • Wang, W.1    Wainwright, M.J.2    Ramchandran, K.3
  • 8
    • 31744440684 scopus 로고    scopus 로고
    • Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information
    • Feb.
    • E. J. Candes, J. K. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Inf. Theory, vol. 52, no. 2, pp. 489-509, Feb. 2006.
    • (2006) IEEE Trans. Inf. Theory , vol.52 , Issue.2 , pp. 489-509
    • Candes, E.J.1    Romberg, J.K.2    Tao, T.3
  • 9
    • 27744468800 scopus 로고    scopus 로고
    • The curvelet representation of wave propagators is optimally sparse
    • Nov.
    • E. J. Candes and L. Demanet, "The curvelet representation of wave propagators is optimally sparse," Comm. Pure Appl. Math., vol. 58, no. 11, pp. 1472-1528, Nov. 2005.
    • (2005) Comm. Pure Appl. Math. , vol.58 , Issue.11 , pp. 1472-1528
    • Candes, E.J.1    Demanet, L.2
  • 10
    • 77949662812 scopus 로고    scopus 로고
    • From theory to practice: Sub-Nyquist sampling of sparse wideband analog signals
    • Apr.
    • M. Mishali and Y. C. Eldar, "From theory to practice: Sub-Nyquist sampling of sparse wideband analog signals," IEEE J. Sel. Topics Signal Process., vol. 4, no. 2, pp. 375-391, Apr. 2010.
    • (2010) IEEE J. Sel. Topics Signal Process. , vol.4 , Issue.2 , pp. 375-391
    • Mishali, M.1    Eldar, Y.C.2
  • 11
  • 12
    • 84907737173 scopus 로고    scopus 로고
    • Compressive sensing by random convolution
    • SIAM Dec.
    • J. Romberg, "Compressive sensing by random convolution," SIAM J. Imag. Sci., vol. 2, no. 4, pp. 1098-1128, Dec. 2009.
    • (2009) J. Imag. Sci. , vol.2 , Issue.4 , pp. 1098-1128
    • Romberg, J.1
  • 15
    • 0001287271 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • R. Tibshirani, "Regression shrinkage and selection via the lasso," J. Roy. Statist. Soc. Ser. B, vol. 58, no. 1, pp. 267-288, 1996.
    • (1996) J. Roy. Statist. Soc. Ser. B , vol.58 , Issue.1 , pp. 267-288
    • Tibshirani, R.1
  • 16
    • 85032751389 scopus 로고    scopus 로고
    • Imaging via compressive sampling
    • Mar.
    • J. Romberg, "Imaging via compressive sampling," IEEE Signal Process. Mag., vol. 25, no. 2, pp. 14-20, Mar. 2008.
    • (2008) IEEE Signal Process. Mag. , vol.25 , Issue.2 , pp. 14-20
    • Romberg, J.1
  • 18
    • 58049195322 scopus 로고    scopus 로고
    • Highly undersampled magnetic resonance image reconstruction via homotopic -0-minimization
    • Jan.
    • J. Trzasko, A. Manduca, and E. Borisch, "Highly undersampled magnetic resonance image reconstruction via homotopic -0-minimization," IEEE Trans. Med. Imag., vol. 28, no. 1, pp. 106-121, Jan. 2009.
    • (2009) IEEE Trans. Med. Imag. , vol.28 , Issue.1 , pp. 106-121
    • Trzasko, J.1    Manduca, A.2    Borisch, E.3
  • 19
    • 77953757231 scopus 로고    scopus 로고
    • Decentralized sparse signal recovery for compressive sleeping wireless sensor networks
    • July
    • Q. Ling and Z. Tian, "Decentralized sparse signal recovery for compressive sleeping wireless sensor networks," IEEE Trans. Signal Process., vol. 58, no. 7, pp. 3816-3827, July 2010.
    • (2010) IEEE Trans. Signal Process. , vol.58 , Issue.7 , pp. 3816-3827
    • Ling, Q.1    Tian, Z.2
  • 20
  • 22
    • 77953866473 scopus 로고    scopus 로고
    • Distributed spectrum sensing for cognitive radio networks by exploiting sparsity
    • Mar.
    • J. A. Bazerque and G. B. Giannakis, "Distributed spectrum sensing for cognitive radio networks by exploiting sparsity," IEEE Trans. Signal Process., vol. 58, no. 3, pp. 1847-1862, Mar. 2010.
    • (2010) IEEE Trans. Signal Process. , vol.58 , Issue.3 , pp. 1847-1862
    • Bazerque, J.A.1    Giannakis, G.B.2
  • 23
    • 79551625541 scopus 로고    scopus 로고
    • A two-step compressed spectrum sensing scheme for wideband cognitive radios
    • Y. Wang, Z. Tian, and C. Feng, "A two-step compressed spectrum sensing scheme for wideband cognitive radios," in Proc. 2010 IEEE GLOBECOM, pp. 1-5.
    • Proc. 2010 IEEE GLOBECOM , pp. 1-5
    • Wang, Y.1    Tian, Z.2    Feng, C.3
  • 24
    • 78951476164 scopus 로고    scopus 로고
    • Distributed compressive spectrum sensing in cooperative multihop cognitive networks
    • Feb.
    • F. Zeng, C. Li, and Z. Tian, "Distributed compressive spectrum sensing in cooperative multihop cognitive networks," IEEE J. Sel. Topics Signal Process., vol. 5, no. 1, pp. 37-48, Feb. 2011.
    • (2011) IEEE J. Sel. Topics Signal Process. , vol.5 , Issue.1 , pp. 37-48
    • Zeng, F.1    Li, C.2    Tian, Z.3
  • 25
    • 0037981898 scopus 로고    scopus 로고
    • Spectrum policy task force report
    • Spectrum Policy Task Force
    • Spectrum Policy Task Force, "Spectrum policy task force report," Federal Communications Commission ET Docket 02-135, 2002.
    • (2002) Federal Communications Commission et Docket , vol.2 , Issue.135


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.