Frequency Estimation of Continuous Signals whith Sub-Nyquist Sampling, through its Maximum Singular Value

Authors

  • Herman Hamilton Guerrero Chapal Universidad Mariana
  • Evelio Astaiza Hoyos Universidad del Quindío

Keywords:

Autocorrelation, Awgn, Sampling frequency, Sub-Nyquist, Singular Values, Cognitive Radio, Spectrum

Abstract

In Cognitive Radio (CR) systems seeks to make an efficient use of radio resources, therefore the Spectrum Sensing (SS) is a critical function, since of the SS function depends that the CR system has an adequate knowledge of the spectral bands sub used. Traditional methods of SS, presents major implementation challenges because they require high sampling rates above the Nyquist rate, doing that the number of samples to be processed is high. To address this problem, in this paper a method for estimating the center frequency of continuous signals is presented, The signal is acquired at lower frequencies established by Nyquist sampling theorem. With the obtained data autocorrelation matrix is calculated, then the singular values of this matrix are obtained and compared with preset values, from these values, the center frequency of the signal is estimated.

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Author Biographies

Herman Hamilton Guerrero Chapal, Universidad Mariana

Ing. Electrónico. Candidato a Magister en Electrónica y Telecomunicaciones Universidad del Cauca. Docente Facultad de Ingeniería, Grupo GRIM Universidad Mariana, Pasto, Colombia. hhguerrero@umariana.edu.co, hermanguerrero@unicauca.edu.co

Evelio Astaiza Hoyos, Universidad del Quindío

Ing. Electrónica y Telecomunicaciones. Mag. en Ingeniería Área Electrónica y Telecomunicaciones. Candidato a Doctor Ciencias de la Electrónica Universidad del Cauca. Docente Facultad de Ingeniería, Grupo GITUQ, Universidad del Quindío, Armenia, Colombia. eastaiza@uniquindio.edu.co

References

J. F. Negrete, E.Páez, G. I. Sánchez, and J. Bravo, " Spectrum Crunch a la Vuelta de la Esquina," MediaTelecom, Tech Rep., May. 2013.

M. A. McHenry, D. McCloskey, D. Roberson, and J. T. McDonald, " Spectrum Occupancy Measurements Chicago, Illinois," Tech Rep., Nov. 2005.

Q. Zaho, B. M. Sadler, “A Survey of Dynamic Spectrum Access: Signal Processing, Networking and Regulatory Policy”, IEEE Signal Processing Magazine, pp. 79 – 89, May 2007.

J. Mitola, “Cognitive radio for flexible mobile multimedia communications,” in Proc. IEEE Int. Workshop Mobile Multimedia Communications, pp. 3–10, 1999.

D. Cabric, S.M. Mishra, and R.W. Brodersen, “Implementation issues in spectrum sensing for cognitive radios,” in Proc. 38th. Asilomar Conf. Signals Systems, Computers, pp. 772–776, 2004.

A. Sonnenschein and P. M. Fishman, “Radiometric detection of spreadspectrum signals in noise of uncertainty power,” IEEE Trans. Aerosp. Electron. Syst., vol. 28, no. 3, pp. 654–660, Jul. 1992.

A. Sahai, D. Cabric, “Spectrum sensing: Fundamental limits and practical challenges,” A tutorial in IEEE Int. Symp. New Frontiers DySPAN, Baltimore, MD, Nov. 2005.

R. Tandra and A. Sahai, “Fundamental limits on detection in low SNR under noise uncertainty,” in Proc. WirelessCom, Maui, HI, Jun. 2005, pp. 464–469.

S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory, vol. 2. Englewood Cliffs, NJ: Prentice–Hall, 1998.

H. Urkowitz, “Energy detection of unknown deterministic signals,” Proc. IEEE, vol. 55, no. 4, pp. 523–531, Apr. 1967.

D. Cabric, A. Tkachenko, and R. W. Brodersen, “Spectrum sensing measurements of pilot, energy, and collaborative detection,” in Proc. MILCOM, Oct. 2006, pp. 1–7.

H.-S. Chen, W. Gao, and D. G. Daut, “Signature based spectrum sensing algorithms for IEEE 802.22 WRAN,” in Proc. IEEE ICC, Jun. 2007, pp. 6487–6492.

W. A. Gardner, “Exploitation of spectral redundancy in cyclostationary signals,” IEEE Signal Process. Mag., vol. 8, no. 2, pp. 14–36, Apr. 1991

W. A. Gardner,W. A. Brown, III, and C.-K. Chen, “Spectral correlation of modulated signals—Part II: Digital modulation,” IEEE Trans. Commun., vol. COM-35, no. 6, pp. 595–601, Jun. 1987.

N. Han, S. H. Shon, J. O. Joo, and J. M. Kim, “Spectral correlation based signal detection method for spectrum sensing in IEEE 802.22 WRAN systems,” in Proc. Int. Conf. Advanced Commun. Technol., Phoenix Park, Korea, Feb. 2006, pp. 1765–1770.

S. Shellhammer and R. Tandra, Performance of the Power Detector With Noise Uncertainty, Jul. 2006, IEEE Std. 802.22-06/0134r0.

J. J. Martínez, "La Descomposición en Valores Singulares (SVD) y Algunas de sus Aplicaciones," La Gaceta de la RSME, vol 8 no. 3 pp. 795-810, 2005.

M. F. Fahim and M. S. Raeen, "SVD Detection for Cognitive Radio Network based on Average of Maximum-Minimum of the ICDF," Internal. Journ. Adv. Comp. Research, vol. 2, no. 3, pp. 182-187, Sep 2012.

M.Hasbullah and H.Suhaidi, "SVD-Based Signal Detector for Cognitive Radio Networks," in 13th Internal. Confer. Modell.and Simul., 2011, pp. 513-517.

N. Chouhan, J. Dipti, and S.V. Charhate, "Cooperative Spectrum Sensing signal detection using SVD Signal Detector for Cognitive Radio," ITSI Transactiosn on Electrical and Electronics Engineering, pp. 31 - 34, 2013.

C.Shannon, "Communication in the presence of noise," Proc. IEEE, vol. 72, no. 9, pp. 1192-1201, Sep. 1984.

G. Castellanos Domínguez and Y. Semenovich Shinakov, " Analisis de Aleatoriedad en Señales y Sistemas," Universidad Nacional de Colombia, Sede Manizales. 2007

J. G. Proakis and D. G. Manolakis, " Digital Signal Processing," Pretience Hall International, Inc. 1996.

Stoica and A. Nehorai, “Statistical efficiency study of direction estimation methods, Part I: Analysis of MUSIC and preliminary study of MLM,” Advances in Spectrum Analysis and Array Processing, S. Haykin, Ed. Englewood Cliffs, NJ: Prentice-Hall, vol. 1, pp. 263-305, 1991.

V.F. Pisarenko, “The retrieval of harmonics from a covariance function'', Geophysics J.Royal Ast. Soc., vol.33, pp.347-366, 1973.

Published

2016-12-30

How to Cite

Guerrero Chapal, H. H., & Astaiza Hoyos, E. (2016). Frequency Estimation of Continuous Signals whith Sub-Nyquist Sampling, through its Maximum Singular Value. Revista Politécnica, 12(23), 57–64. Retrieved from https://revistas.elpoli.edu.co/index.php/pol/article/view/899

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