A review on energy based spectrum sensing in Cognitive Radio Networks

Cognitive Radio Networks is considered as the solution to the problem of limited bandwidth which arises in the wireless networks. Spectrum sensing is an important issue of CRNs. Spectrum sensing involves the sensing of the licensed user signal, then allowing the unlicensed user to use the free spectrum band in the network. The energy based spectrum sensing techniques in CRNs become important in battery oriented applications. This paper focuses on some existing researches on energy based spectrum sensing. Many factors which play an important role in the sensing process have also been explained.

[1]  Ali El-Hajj,et al.  Blind and robust spectrum sensing based on RF impairments mitigation for cognitive radio receivers , 2014, 2014 International Conference on High Performance Computing & Simulation (HPCS).

[2]  Mikko Valkama,et al.  Maximum-minimum energy based spectrum sensing under frequency selectivity for Cognitive Radios , 2014, 2014 9th International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM).

[3]  Huan X. Nguyen,et al.  An efficient hybrid double-threshold based energy detection for cooperative spectrum sensing , 2014, 2014 27th Biennial Symposium on Communications (QBSC).

[4]  Ehab Mahmoud Mohamed,et al.  Improved Cognitive Radio energy detection algorithm based upon noise uncertainty estimation , 2014, 2014 31st National Radio Science Conference (NRSC).

[5]  Mehdi Mahdavi,et al.  Analysis of a New Energy-Based Sensor Selection Method for Cooperative Spectrum Sensing in Cognitive Radio Networks , 2014, IEEE Sensors Journal.

[6]  Mauro Barni,et al.  Multiple-observation hypothesis testing under adversarial conditions , 2013, 2013 IEEE International Workshop on Information Forensics and Security (WIFS).

[7]  Luc Vandendorpe,et al.  Max-Min SNR Signal Energy Based Spectrum Sensing Algorithms for Cognitive Radio Networks with Noise Variance Uncertainty , 2013, IEEE Transactions on Wireless Communications.

[8]  Jasvir Singh,et al.  Trade-off between AND and OR Detection method for Cooperative Sensing in Cognitive Radio , 2014, 2014 IEEE International Advance Computing Conference (IACC).

[9]  A. Sonnenschein,et al.  Radiometric detection of spreadspectrum signals in noise of uncertain power , 1992 .

[10]  Shiyu Xu,et al.  Spectrum Sensing Based on Cyclostationarity , 2008, 2008 Workshop on Power Electronics and Intelligent Transportation System.

[11]  Renu Vig,et al.  Optimization of secondary user access in cognitive radio networks , 2014, 2014 Recent Advances in Engineering and Computational Sciences (RAECS).

[12]  David G. Daut,et al.  Signature Based Spectrum Sensing Algorithms for IEEE 802.22 WRAN , 2007, 2007 IEEE International Conference on Communications.

[13]  Mauro Barni,et al.  Binary Hypothesis Testing Game With Training Data , 2013, IEEE Transactions on Information Theory.

[14]  Tharmalingam Ratnarajah,et al.  Throughput analysis using eigenvalue based spectrum sensing under noise uncertainty , 2012, 2012 8th International Wireless Communications and Mobile Computing Conference (IWCMC).

[15]  Sungsoo Park,et al.  Spectrum Sensing Optimization for Energy-Harvesting Cognitive Radio Systems , 2014, IEEE Transactions on Wireless Communications.

[16]  Renu Vig,et al.  Optimization of SU's probability of false alarm for dynamic spectrum access in cognitive radio , 2014, 2014 International Conference on Computing for Sustainable Global Development (INDIACom).

[17]  Anant Sahai,et al.  SNR Walls for Signal Detection , 2008, IEEE Journal of Selected Topics in Signal Processing.

[18]  Erik G. Larsson,et al.  Primary System Detection for Cognitive Radio: Does Small-Scale Fading Help? , 2007, IEEE Communications Letters.

[19]  Fabrice Labeau,et al.  On Signal Detection in the Presence of Weakly Correlated Noise over Fading Channels , 2014, IEEE Transactions on Communications.

[20]  Kevin W. Sowerby,et al.  Spectrum sensing using principal component analysis , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[21]  Mauro Barni,et al.  The Source Identification Game: An Information-Theoretic Perspective , 2013, IEEE Transactions on Information Forensics and Security.