Iterative Cyclostationarity-Based Feature Detection of Multiple Primary Signals for Spectrum Sharing Scenarios

Harada, Hiroyuki; Fujii, Hiromasa; Furuno, T.; Miura, S.; Ohya, Tomoyuki

doi:10.1109/dyspan.2010.5457868

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…We proposed iterative cyclostationarity-based feature detection in order to solve the above problem [12]. This detection method eliminates the CAF peak of the strong signal when computing the covariance matrix for the weak signal,Σ α1…”

Section: B Iterative Cyclostationarity-based Feature Detectionmentioning

confidence: 99%

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Experimental evaluation of cyclostationarity-based multiple signal identification method by using spatial channel emulator

Harada

Fujii

Miura

et al. 2011

2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)

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An important and widely used detection technique is cyclostationarity-based feature detection because the method does not require prior information such as the signal bandwidth or frame format, and time and frequency synchronization are likewise not required. The problem with conventional cyclostationaritybased feature detection is that the detection probability of weak signals degrades if multiple signals with different received-power levels are captured simultaneously. One way to address this problem is to use a multiple signal identification method in which appropriate notches suppress the effects of other signals. In this paper, we evaluate a multiple signal identification method based on test bed experiments. In order to evaluate the method in a realistic environment as a field test, a spatial channel emulator and an antenna of a mock terminal are applied to the test bed. The results reveal the effectiveness of the methodology in realistic spectrum sharing scenarios.

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Section: B Iterative Cyclostationarity-based Feature Detectionmentioning

confidence: 99%

“…To address this problem, multiple signal identification methods have been studied. In [12], iterative cyclostationaritybased feature detection was proposed. This method suppresses the effects of previously-detected signals in the CAF domain, and improves the detection probability of weak signals.…”

Section: Introductionmentioning

confidence: 99%

Experimental evaluation of cyclostationarity-based multiple signal identification method by using spatial channel emulator

Harada

Fujii

Miura

et al. 2011

2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)

Self Cite

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show abstract

“…We proposed iterative cyclostationarity-based feature detection in order to solve the above problem [11].…”

Section: B Iterative Cyclostationarity-based Feature Detectionmentioning

confidence: 99%

“…In [11], iterative cyclostationarity-based feature detection was proposed to address this problem. This multiple signal identification method suppresses the effects of previously-detected signals in the CAF domain, and improves the detection probability of weak signals.…”

Section: Introductionmentioning

confidence: 99%

Experimental evaluation of multiple signal identification based on cyclostationarity in spectrum sharing scenarios

Harada¹,

Fujii²,

Miura³

et al. 2010

2010 16th Asia-Pacific Conference on Communications (APCC)

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An important and widely used detection technique is cyclostationarity-based feature detection because the method does not require prior information such as the signal bandwidth or frame format, and time and frequency synchronization are likewise not required. The problem with conventional cyclostationarity-based feature detection is that the detection probability of weak signals degrades if multiple signals with different received-power levels are captured simultaneously. Multiple signal identification has been studied in order to solve such a problem. The iterative detection method suppresses the effects of previously-detected signals in the cyclic auto-correlation domain, and so improves the detection probability of weak signals. In this paper, the multiple signal identification method is evaluated based on testbed experiments. In addition, the modification of the multiple signal identification method in which the effects of other signals are previously-relieved is proposed and applied to the testbed instead of the iterative detection method. The detection performance levels of the conventional and proposed detection methods are evaluated and compared to the results of computer simulations. The results reveal the effectiveness of the proposed detection method in spectrum sharing scenarios.

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Rigorous Analysis on the Sensitivity of Cyclostationary Detection

Zeng

2017

2017 IEEE Wireless Communications and Networking Conference (WCNC)

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Iterative Cyclostationarity-Based Feature Detection of Multiple Primary Signals for Spectrum Sharing Scenarios

Cited by 4 publications

References 9 publications

Experimental evaluation of cyclostationarity-based multiple signal identification method by using spatial channel emulator

Experimental evaluation of cyclostationarity-based multiple signal identification method by using spatial channel emulator

Experimental evaluation of multiple signal identification based on cyclostationarity in spectrum sharing scenarios

Rigorous Analysis on the Sensitivity of Cyclostationary Detection

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