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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

The complementary ROC curves for ED and GD.
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sensors-15-16105-f007: The complementary ROC curves for ED and GD.

Mentions: The complementary receiver operating characteristic (ROC) curves, which are widely used in practice, for example in [39,40,41], for the ED and GD are presented in Figure 7 with and without the noise power uncertainty atand. In a general, for both detectors the noise power uncertainty leads to the complementary ROC curves shifting away from the (0,0) origin. As shown in Figure 7, the GD demonstrates the better sensing performance in comparison with the ED and the sensing performance degradation rate of GD is less under the noise power uncertainty conditions. In the GD case, under the low SNR or if the SNR is above the, the sensing performance degradation caused by the noise power uncertainty can be compensated by increasing in the number of samples N. However, if the SNR is below the, the ED complementary ROC curve is over the dotted straight line corresponding to the random coin-tossing detector case in Figure 7. This situation is observed atdB,dB ifdB (Figure 5) anddB,dB when (Figure 6).


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

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

The complementary ROC curves for ED and GD.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-16105-f007: The complementary ROC curves for ED and GD.
Mentions: The complementary receiver operating characteristic (ROC) curves, which are widely used in practice, for example in [39,40,41], for the ED and GD are presented in Figure 7 with and without the noise power uncertainty atand. In a general, for both detectors the noise power uncertainty leads to the complementary ROC curves shifting away from the (0,0) origin. As shown in Figure 7, the GD demonstrates the better sensing performance in comparison with the ED and the sensing performance degradation rate of GD is less under the noise power uncertainty conditions. In the GD case, under the low SNR or if the SNR is above the, the sensing performance degradation caused by the noise power uncertainty can be compensated by increasing in the number of samples N. However, if the SNR is below the, the ED complementary ROC curve is over the dotted straight line corresponding to the random coin-tossing detector case in Figure 7. This situation is observed atdB,dB ifdB (Figure 5) anddB,dB when (Figure 6).

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