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SNR Wall Effect Alleviation by Generalized Detector Employed in Cognitive Radio Networks.

Shbat MS, Tuzlukov V - Sensors (Basel) (2015)

Bottom Line: The most commonly used spectrum sensing techniques in cognitive radio (CR) networks, such as the energy detector (ED), matched filter (MF), and others, suffer from the noise uncertainty and signal-to-noise ratio (SNR) wall phenomenon.These detectors cannot achieve the required signal detection performance regardless of the sensing time.The simulation results confirm our theoretical issues and effectiveness of GD implementation in CR networks based on antenna array.

View Article: PubMed Central - PubMed

Affiliation: School of Electronics Engineering, College of IT Engineering, Kyungpook National University, 1370 Sankyuk-dong, Buk-gu, Daegu 702-701, Korea. modboss80@gmail.com.

ABSTRACT
The most commonly used spectrum sensing techniques in cognitive radio (CR) networks, such as the energy detector (ED), matched filter (MF), and others, suffer from the noise uncertainty and signal-to-noise ratio (SNR) wall phenomenon. These detectors cannot achieve the required signal detection performance regardless of the sensing time. In this paper, we explore a signal processing scheme, namely, the generalized detector (GD) constructed based on the generalized approach to signal processing (GASP) in noise, in spectrum sensing of CR network based on antenna array with the purpose to alleviate the SNR wall problem and improve the signal detection robustness under the low SNR. The simulation results confirm our theoretical issues and effectiveness of GD implementation in CR networks based on antenna array.

No MeSH data available.


Related in: MedlinePlus

Spectrum sensing performance for the ED and GD in terms of the probability of error as a function of the sample number.
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sensors-15-16105-f008: Spectrum sensing performance for the ED and GD in terms of the probability of error as a function of the sample number.

Mentions: In Figure 8, a comparison between the ED and GD performance in terms of the probability of erroras a function of the sample number N, the analogous performance is discussed in [36], is shown atdB,dB, anddB. The GD demonstrates the better sensing performance in comparison with the ED one. For example, atthe probability of erroris equal to 0.3126 in the GD case and 0.5346 in the ED case. AtdB that corresponds to thewhendB, we can see that the probability of errorin the ED case fails to be robust and is distinctly differed owing to the SNR wall phenomenon. In this case, an increasing in the number of samples N is not effective to improve the probability of errorperformance for ED. At the same time, the GD has the same normal behavior meaning that the probability of errorperformance for GD is improved with increasing in the number of samples N.


SNR Wall Effect Alleviation by Generalized Detector Employed in Cognitive Radio Networks.

Shbat MS, Tuzlukov V - Sensors (Basel) (2015)

Spectrum sensing performance for the ED and GD in terms of the probability of error as a function of the sample number.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541870&req=5

sensors-15-16105-f008: Spectrum sensing performance for the ED and GD in terms of the probability of error as a function of the sample number.
Mentions: In Figure 8, a comparison between the ED and GD performance in terms of the probability of erroras a function of the sample number N, the analogous performance is discussed in [36], is shown atdB,dB, anddB. The GD demonstrates the better sensing performance in comparison with the ED one. For example, atthe probability of erroris equal to 0.3126 in the GD case and 0.5346 in the ED case. AtdB that corresponds to thewhendB, we can see that the probability of errorin the ED case fails to be robust and is distinctly differed owing to the SNR wall phenomenon. In this case, an increasing in the number of samples N is not effective to improve the probability of errorperformance for ED. At the same time, the GD has the same normal behavior meaning that the probability of errorperformance for GD is improved with increasing in the number of samples N.

Bottom Line: The most commonly used spectrum sensing techniques in cognitive radio (CR) networks, such as the energy detector (ED), matched filter (MF), and others, suffer from the noise uncertainty and signal-to-noise ratio (SNR) wall phenomenon.These detectors cannot achieve the required signal detection performance regardless of the sensing time.The simulation results confirm our theoretical issues and effectiveness of GD implementation in CR networks based on antenna array.

View Article: PubMed Central - PubMed

Affiliation: School of Electronics Engineering, College of IT Engineering, Kyungpook National University, 1370 Sankyuk-dong, Buk-gu, Daegu 702-701, Korea. modboss80@gmail.com.

ABSTRACT
The most commonly used spectrum sensing techniques in cognitive radio (CR) networks, such as the energy detector (ED), matched filter (MF), and others, suffer from the noise uncertainty and signal-to-noise ratio (SNR) wall phenomenon. These detectors cannot achieve the required signal detection performance regardless of the sensing time. In this paper, we explore a signal processing scheme, namely, the generalized detector (GD) constructed based on the generalized approach to signal processing (GASP) in noise, in spectrum sensing of CR network based on antenna array with the purpose to alleviate the SNR wall problem and improve the signal detection robustness under the low SNR. The simulation results confirm our theoretical issues and effectiveness of GD implementation in CR networks based on antenna array.

No MeSH data available.


Related in: MedlinePlus