References
- M. Alink et al., Lowering the SNR wall for energy detection using cross-correlation, IEEE Trans. Veh. Technol. 60 (2011), no. 8, 3748-3756. https://doi.org/10.1109/TVT.2011.2165569
- W. Gardner, Exploitation of spectral redundancy in cyclostationary signals, IEEE Signal Process. Mag. 8 (1991), 14-31. https://doi.org/10.1109/79.81007
- Y. Zeng and Y. Liang, Eigenvalue-based spectrum sensing algorithms for cognitive radio, IEEE Trans. Commun. 57 (2009), no. 6, 1784-1793. https://doi.org/10.1109/TCOMM.2009.06.070402
- R. Tandra and A. Sahai, SNR walls for signal detection, IEEE J. Sel. Topics Signal Process 2 (2008), no. 1, 4-17. https://doi.org/10.1109/JSTSP.2007.914879
- Y. Liang et al., Cognitive radio networking and communications: an overview, IEEE Trans. Veh. Technol. 60 (2011), no. 7, 3386-3407. https://doi.org/10.1109/TVT.2011.2158673
- D. Martinez and A. Andrade, Reducing the effects of the noise uncertainty in energy detectors for cognitive radio networks, Int. J. Commun. Syst. 30 (2017), no. 1, e2907. https://doi.org/10.1002/dac.2907
- S. Nallagonda et al., Censoring-based cooperative spectrum sensing with improved energy detectors and multiple antennas in fading channels, IEEE Trans. Aerosp. Electron. Syst. 54 (2018), no. 2, 537-553. https://doi.org/10.1109/TAES.2017.2732798
- T. Bogale et al., Wide-band sensing and optimization for cognitive radio networks with noise variance uncertainty, IEEE Trans. Commun. 63 (2015), no. 4, 1091-1105. https://doi.org/10.1109/TCOMM.2015.2394390
- T. Bogale and L. Vandendorpe, Linearly combined signal energy based spectrum sensing algorithm for cognitive radio networks with noise variance uncertainty, in Proc. IEEE Conf. CROWNCOM, Washington, DC, USA, 2013, pp. 80-86.
- L. Zhang et al., Spectrum sensing under spectrum misuse behaviors: A multi-hypothesis test perspective, IEEE Trans. Inf. Forensics Security 13 (2018), no. 4, 993-1007. https://doi.org/10.1109/TIFS.2017.2774770
- C. Chen H. Cheng and Y. Yao, Cooperative spectrum sensing in cognitive radio networks in the presence of the primary user emulation attack, IEEE Trans. Wireless Commun. 10 (2011), no. 7, 2135-2141. https://doi.org/10.1109/TWC.2011.041311.100626
- H. Rohling, Radar CFAR thresholding in clutter and multiple target situations, IEEE Trans. Aerosp. Electron. Syst. ASE-19 (1983), no. 4, 608-621. https://doi.org/10.1109/TAES.1983.309350
- N. Levanon, Detection loss due to interfering targets in ordered statistics CFAR, IEEE Trans. Aerosp. Electron. Syst. ASE-24 (1988), 678-681. https://doi.org/10.1109/7.18634
- C.-J. Kim D.-S. Han, and H.-S. Lee, Generalized OS CFAR detector with noncoherent integration, Signal Process. 31 (1983), no. 1, 43-56. https://doi.org/10.1016/0165-1684(93)90100-O
- C.-J. Kim and H.-S. Lee, Analysis of the generalized order statistics constant false alarm detector, ETRI J. 16 (1994), no. 1, 17-34. https://doi.org/10.4218/etrij.94.0194.0012
- L. Shen et al., Blind spectrum sensing for cognitive radio channels with noise uncertainty, IEEE Trans. Wireless Commun. 10 (2011), no. 6, 1721-1724. https://doi.org/10.1109/TWC.2011.040511.101559
- S. Rostami et al., Order-statistic based spectrum sensing for cognitive radio, IEEE Trans. Commun. Lett. 16 (2012), no. 5, 592-595. https://doi.org/10.1109/LCOMM.2012.030512.111887
- P. K. Varsheny. Distributed detection and data fusion, Springer‐Verlag, New York, USA, 1997.
- A. Ghasemi and E. S. Sousa, Collaborative spectrum sensing for opportunistic access in fading environments, in Proc. 1st IEEE Symposium New Frontiers Dynamic Spectrum Access Network (DySPAN), Baltimore, MD, USA, Nov. 8-11, 2005, pp. 131-136.
- W. Zhang, R. K. Mallik, and K. B. Letaief, Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks, IEEE Trans. Wireless Commun. 8 (2009), no. 12, 5761-5766. https://doi.org/10.1109/TWC.2009.12.081710
- K. Letaief and W. Zhang, Cooperative communications for cognitive radio networks, Proc. IEEE 97 (2009), no. 5, 878-893. https://doi.org/10.1109/JPROC.2009.2015716
- A. Vempaty, L. Tong, and P. K. Varsheny, Distributed inference with byzantine data: State-of-the-art review on data falsification attacks, IEEE Signal Process. Mag. 30 (2013), no. 5, 65-75. https://doi.org/10.1109/MSP.2013.2262116
- L. Zhang, et al., Byzantine attack and defense in cognitive radio networks: A survey, IEEE Commun. Surveys Tuts. 17 (2015), no. 3, 1342-1363. https://doi.org/10.1109/COMST.2015.2422735
- G. Ding, Robust spectrum sensing with crowd sensors, IEEE Trans. Commun. 62 (2014), no. 9, 3129-3143. https://doi.org/10.1109/TCOMM.2014.2346775
- R. Chen, J.‐M. Park, and K. Brian, Robust distributed spectrum sensing in cognitive radio networks, in Proc. IEEE INFOCOM, Pheonix, AZ, USA, Apr. 2008, pp. 1-7.
- C.-J. Kim, H.-S. Lee, H.-J. Lee, Adaptive acquisition of PN sequences for DSSS communications, IEEE Trans. Commun. 46 (1998), no. 8, 993-996. https://doi.org/10.1109/26.705393
- C.-J. Kim, et al., Acquisition of PN code with adaptive threshold for DS/SS communications, Electron. Lett. 33 (1997), no.16, 1352-1354. https://doi.org/10.1049/el:19970916
- C.-J. Kim, Adaptive acquisition of PN code in multipath fading mobile channels, Electron. Lett. 38 (2002), no. 2, 135-137. https://doi.org/10.1049/el:20020094
- S. Blake, OS CFAR theory for multiple targets and non-uniform clutter, IEEE Trans. Aerosp. Electron. Syst. 24 (1988), no. 6, 785-790. https://doi.org/10.1109/7.18645
Cited by
- Analysis study and SDR implementation of GoF‐based spectrum sensing for cognitive radio vol.14, pp.5, 2019, https://doi.org/10.1049/iet-com.2019.0711