Efficient detection of FSK-signals based on cyclic statistics

Yi Zhou; Khalid Qaraqe; Erchin Serpedin; Octavia Dobre

doi:10.1109/ICCOMM.2010.5509111

Efficient detection of FSK-signals based on cyclic statistics

Yi Zhou^*, Khalid Qaraqe, Erchin Serpedin, Octavia Dobre

^*Corresponding author for this work

Research output: Contribution to conference › Paper › peer-review

Abstract

Cognitive radios represent a powerful technology for improving the utilization of radio spectrum resources. Detection of low signal-to-noise ratio (SNR) signals with relaxed a priori information on the signal parameters is of high importance for cognitive radios. This paper proposes a detection algorithm based on the first-order cyclostationarity (or cyclic statistics) for frequency shift keying (FSK) signals that only requires partial knowledge on the signal bandwidth, carrier frequency and symbol rate. The results of both theoretical asymptotic analysis and computer simulations are presented. It is shown that the proposed algorithm performs well at low SNRs.

Original language	English
Pages	339-342
Number of pages	4
DOIs	https://doi.org/10.1109/ICCOMM.2010.5509111
Publication status	Published - 2010
Externally published	Yes
Event	8th International Conference on Communications, COMM 2010 - Bucharest, Romania Duration: 10 Jun 2010 → 12 Jun 2010

Conference

Conference	8th International Conference on Communications, COMM 2010
Country/Territory	Romania
City	Bucharest
Period	10/06/10 → 12/06/10

Keywords

Cognitive radio
Cyclostationarity
Frequency shift keying
Signal detection

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10.1109/ICCOMM.2010.5509111

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abstract = "Cognitive radios represent a powerful technology for improving the utilization of radio spectrum resources. Detection of low signal-to-noise ratio (SNR) signals with relaxed a priori information on the signal parameters is of high importance for cognitive radios. This paper proposes a detection algorithm based on the first-order cyclostationarity (or cyclic statistics) for frequency shift keying (FSK) signals that only requires partial knowledge on the signal bandwidth, carrier frequency and symbol rate. The results of both theoretical asymptotic analysis and computer simulations are presented. It is shown that the proposed algorithm performs well at low SNRs.",

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language = "English",

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AU - Zhou, Yi

AU - Qaraqe, Khalid

AU - Serpedin, Erchin

AU - Dobre, Octavia

PY - 2010

Y1 - 2010

N2 - Cognitive radios represent a powerful technology for improving the utilization of radio spectrum resources. Detection of low signal-to-noise ratio (SNR) signals with relaxed a priori information on the signal parameters is of high importance for cognitive radios. This paper proposes a detection algorithm based on the first-order cyclostationarity (or cyclic statistics) for frequency shift keying (FSK) signals that only requires partial knowledge on the signal bandwidth, carrier frequency and symbol rate. The results of both theoretical asymptotic analysis and computer simulations are presented. It is shown that the proposed algorithm performs well at low SNRs.

AB - Cognitive radios represent a powerful technology for improving the utilization of radio spectrum resources. Detection of low signal-to-noise ratio (SNR) signals with relaxed a priori information on the signal parameters is of high importance for cognitive radios. This paper proposes a detection algorithm based on the first-order cyclostationarity (or cyclic statistics) for frequency shift keying (FSK) signals that only requires partial knowledge on the signal bandwidth, carrier frequency and symbol rate. The results of both theoretical asymptotic analysis and computer simulations are presented. It is shown that the proposed algorithm performs well at low SNRs.

KW - Cognitive radio

KW - Cyclostationarity

KW - Frequency shift keying

KW - Signal detection

UR - http://www.scopus.com/inward/record.url?scp=77955651353&partnerID=8YFLogxK

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DO - 10.1109/ICCOMM.2010.5509111

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EP - 342

T2 - 8th International Conference on Communications, COMM 2010

Y2 - 10 June 2010 through 12 June 2010

ER -

Efficient detection of FSK-signals based on cyclic statistics

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Keywords

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