A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks
Abstract
:1. Introduction
2. System Model
3. Proposed Scheme
3.1. Outlier Detection
3.1.1. Step One: Averaging Differences of the SUs
3.1.2. Step Two: SUs’ Correlation
3.1.3. Step Three: Outlier Classification Using the Box-Whisker Plot
4. Numerical Evaluation
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Parameters | Values |
---|---|
Number of SUs | 10 |
Number of OMUs | 1 |
Number of ROMUs | 1 |
Signal-to-noise ratio (SNR) [dB] | −30 to −20 |
Number of iteration | 10,000 |
Samples in each sensing interval | 270 |
Sensing time | 1 ms |
SNR (dB) | Min | Q1 | Median | Q3 | Max | IQR | Lower Limit | Upper Limit |
---|---|---|---|---|---|---|---|---|
−30 | −0.11872 | 0.027923 | 0.029733 | 0.033575 | 0.036673 | 0.005652 | 0.019445 | 0.042053 |
−28 | −0.11368 | 0.024431 | 0.029003 | 0.032603 | 0.038683 | 0.008172 | 0.012172 | 0.044861 |
−26 | −0.1143 | 0.023746 | 0.026274 | 0.033884 | 0.043767 | 0.010139 | 0.008538 | 0.049092 |
−24 | −0.13541 | 0.028492 | 0.035867 | 0.040777 | 0.041255 | 0.012285 | 0.010063 | 0.059205 |
−22 | −0.14429 | 0.03397 | 0.040021 | 0.042547 | 0.045457 | 0.008577 | 0.021104 | 0.055413 |
−20 | −0.17651 | 0.04133 | 0.048643 | 0.052537 | 0.061966 | 0.011206 | 0.024521 | 0.069346 |
SNR (dB) | Min | Q1 | Median | Q3 | Max | IQR | Lower Limit | Upper Limit |
---|---|---|---|---|---|---|---|---|
−30 | −0.04204 | 0.004687 | 0.00771 | 0.013285 | 0.020143 | 0.008598 | −0.00821 | 0.026181 |
−28 | −0.04186 | 0.006307 | 0.009428 | 0.011756 | 0.016341 | 0.005449 | −0.00187 | 0.019929 |
−26 | −0.05041 | 0.003967 | 0.010962 | 0.01545 | 0.021564 | 0.011483 | −0.01326 | 0.032674 |
−24 | −0.0499 | 0.01026 | 0.01173 | 0.013742 | 0.018565 | 0.003482 | 0.005036 | 0.018966 |
−22 | −0.05722 | 0.007603 | 0.013448 | 0.017124 | 0.022818 | 0.009521 | −0.00668 | 0.031406 |
−20 | −0.06726 | 0.009589 | 0.017555 | 0.019618 | 0.021469 | 0.010028 | −0.00545 | 0.03466 |
SNR (dB) | Min | Q1 | Median | Q3 | Max | IQR | Lower Limit | Upper Limit |
---|---|---|---|---|---|---|---|---|
−30 | −0.1233 | 0.01559183 | 0.02097 | 0.023847249 | 0.025981888 | 0.008255 | 0.003209 | 0.03623 |
−28 | −0.12418 | 0.01502566 | 0.02049 | 0.022928377 | 0.03319715 | 0.007903 | 0.003172 | 0.034782 |
−26 | −0.12967 | 0.01767262 | 0.02225 | 0.0264105 | 0.029608583 | 0.008738 | 0.004566 | 0.039517 |
−24 | −0.14605 | 0.02419445 | 0.02566 | 0.030521757 | 0.031995221 | 0.006327 | 0.014703 | 0.040013 |
−22 | −0.15155 | 0.01600466 | 0.02709 | 0.031661185 | 0.035777566 | 0.015657 | −0.00748 | 0.055146 |
−20 | −0.1768 | 0.0300924 | 0.03288 | 0.033382178 | 0.038434105 | 0.00329 | 0.025158 | 0.038317 |
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Khan, M.S.; Faisal, M.; Kim, S.M.; Ahmed, S.; St-Hilaire, M.; Kim, J. A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks. Appl. Sci. 2021, 11, 2362. https://doi.org/10.3390/app11052362
Khan MS, Faisal M, Kim SM, Ahmed S, St-Hilaire M, Kim J. A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks. Applied Sciences. 2021; 11(5):2362. https://doi.org/10.3390/app11052362
Chicago/Turabian StyleKhan, Muhammad Sajjad, Mohammad Faisal, Su Min Kim, Saeed Ahmed, Marc St-Hilaire, and Junsu Kim. 2021. "A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks" Applied Sciences 11, no. 5: 2362. https://doi.org/10.3390/app11052362
APA StyleKhan, M. S., Faisal, M., Kim, S. M., Ahmed, S., St-Hilaire, M., & Kim, J. (2021). A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks. Applied Sciences, 11(5), 2362. https://doi.org/10.3390/app11052362