Consecutive mean excision algorithm

Henttu, P.; Aromaa, S.

doi:10.1109/isssta.2002.1048582

Cited by 54 publications

(29 citation statements)

References 5 publications

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“…From the analysis in Section II, we know that the detection process can be divided into two parts: First, calculate the threshold parameter h T , that is the work of CME algorithm [4][5][6]; and the second, construct the detector and make the decision.…”

Section: Signal Existence Detection Algorithmmentioning

confidence: 99%

Consecutive Mean Excision Based Signal Existence Detection in AWGN

Zhang¹,

Luo²,

Zhou³

2009

2009 5th International Conference on Wireless Communications, Networking and Mobile Computing

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This paper treats the problem of signal existence detection of universal signals in additive white Gaussian noise (AWGN) condition from the new angle. The signal is seen as 'interference' and the consecutive mean excision (CME) algorithm is used to finding out the 'interference'. Any a priori information about the signal and the noise is not required. The performance of the detector is analyzed and an equation is gained to explain the influence of Signal Power to Noise Power Ratio (SNR) on the probability of detection. Monte Carlo computer simulations are carried out and detailed discussions are made for each test. The results verify that the proposed method could detect the signal with detection probability 1 when the SNR is above 0dB.

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Section: Signal Existence Detection Algorithmmentioning

confidence: 99%

Consecutive Mean Excision Based Signal Existence Detection in AWGN

Zhang¹,

Luo²,

Zhou³

2009

2009 5th International Conference on Wireless Communications, Networking and Mobile Computing

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“…After the computation of the ordinary Fourier transform and its coding gain the bandwidth of the interference is determined using the consecutive mean excision (CME) algorithm for interference localization [7]. The CME algorithm is a blind, robust algorithm for localizing outliers (samples whose statistical properties differ from the desired set).…”

Section: Interference Suppression Algorithmmentioning

confidence: 99%

Transform-selective interference suppression algorithm for spread-spectrum communications

Aromaa

Henttu

Juntti

2005

IEEE Signal Process. Lett.

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An adaptive method for suppressing interference with an unknown model is presented. The method is based on computation of several transforms in parallel and selecting the most suitable one depending on a priori unknown the interference type based on a compression gain (CG) metric, which is related to the interference concentration in the transform domain. It is also possible to estimate the a priori parameters required by some transforms. The method can be expanded to utilize an arbitrary number of transforms. It is shown through computer simulations that the CG is a good metric for choosing the proper domain for interference excision.

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“…But the calculation of the median value causes a complex operation because of the sorting of data. The CME [4] algorithm proposed by Henttu and the FCME [5] proposed by Vartianinen can provide better performance in various interference environment. However, when the JSR is near 25dB and the percentage of the relative band width is over 30%, the performance of these two algorithms is deteriorating rapidly.…”

Section: Introductionmentioning

confidence: 99%

Work in progress: Iterative threshold setting strategy based on second-order statistics for interference suppression in frequency domain

Liu

Wang

et al. 2014

9th International Conference on Communications and Networking in China

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A new robust threshold setting strategy based on the second-order statistics, which is applied to the model of frequency domain interference suppression (IS) in DSSS communication system, is proposed. The predefined scaling factor is derived according to the distribution characteristic of Rayleigh distribution, which the magnitude spectrum of DS received signal obeys approximately. The threshold is calculated by the second-order statistics of the signal magnitude spectrum combined with the first-order statistics. The new algorithm is more constringent with the iteration. Both theoretical analysis and simulations illustrate that, the new method has good suppression effect to the narrowband interference when the jammer to signal ratio (JSR) goes to 50dB and the percentage of signal bandwidth corrupted reaches 40%.

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Consecutive mean excision algorithm

Cited by 54 publications

References 5 publications

Consecutive Mean Excision Based Signal Existence Detection in AWGN

Consecutive Mean Excision Based Signal Existence Detection in AWGN

Transform-selective interference suppression algorithm for spread-spectrum communications

Work in progress: Iterative threshold setting strategy based on second-order statistics for interference suppression in frequency domain

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