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An Efficient Optimized Handover in Cognitive Radio Networks using Cooperative Spectrum Sensing


Cognitive radio systems necessitate the incorporation of cooperative spectrum sensing among cognitive users to increase the reliability of detection. We have found that cooperative spectrum sensing is not only advantageous, but is also essential to avoid interference with any primary users. Interference by licensed users becomes a chief concern and issue, which affects primary as well as secondary users leading to restrictions in spectrum sensing in cognitive radios. When the number of cognitive users increases, the overheads of the systems, which are meant to report the sensing results to the common receiver, which becomes massive. When the spectrum, which is in use becomes unavailable or when the licensed user takes the allocated band, these networks have the capability of changing their operating frequencies. In addition, cognitive radio networks are seen to have the unique capability of sensing the spectrum range and detecting any spectrum, which has been left underutilized. Further this capability of recognizing the spectrum range based on the dimensions detected, allows for determination of the band, which may be utilized. The main objective of this paper is to analyze the cognitive radio's spectrum sensing ability and evolving a self-configured system with dynamic intelligence networks without causing any interference to the primary user. The paper also brings focus to the quantitative analysis of the two spectrum sensing techniques namely; Energy Detection and Band Limited White Noise Detection. The estimation technique for detecting spectrum noise is based on the detection of probability and probability of false alarms at different Signal-to-Noise Ratio (SNR) levels using Additive White Gaussian Noise signal (AWGN). The efficiency of the proposed Cooperative CUSUM spectrum sensing algorithm performs better than existing optimal rules based on a single observation spectrum sensing techniques under cooperative networks.



Total Pages: 9


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Akyildiz, I.F. et al. "A Survey on Spectrum Management in Cognitive Radio Networks." IEEE Communications Magazine 46.4 (2008): 40-48. Crossref. Web.

Anandakumar. "ENERGY EFFICIENT NETWORK SELECTION USING 802.16G BASED GSM TECHNOLOGY." Journal of Computer Science 10.5 (2014): 745-754. Crossref. Web.

Anandakumar, H., and K. Umamaheswari. "Supervised Machine Learning Techniques in Cognitive Radio Networks During Cooperative Spectrum Handovers." Cluster Computing 20.2 (2017): 1505-1515. Crossref. Web.

Crow, B.P. et al. "IEEE 802.11 Wireless Local Area Networks." IEEE Communications Magazine 35.9 (1997): 116-126. Crossref. Web.

Gao, Zhaoyu et al. "Security and Privacy of Collaborative Spectrum Sensing in Cognitive Radio Networks." IEEE Wireless Communications 19.6 (2012): 106-112. Crossref. Web.

Haykin, S. "Cognitive Radio: Brain-Empowered Wireless Communications." IEEE Journal on Selected Areas in Communications 23.2 (2005): 201-220. Crossref. Web.

Jeongkeun Lee et al. "Understanding Interference and Carrier Sensing in Wireless Mesh Networks." IEEE Communications Magazine 47.7 (2009): 102-109. Crossref. Web.

Lu, Dianjie et al. "Interference-Aware Spectrum Handover for Cognitive Radio Networks." Wireless Communications and Mobile Computing 14.11 (2012): 1099-1112. Crossref. Web.

Pei, Qing-Qi, Zi Li, and Li-Chuan Ma. "A Trust Value-Based Spectrum Allocation Algorithm in CWSNs." International Journal of Distributed Sensor Networks 9.5 (2013): 261264. Crossref. Web.

Sarathambekai, S., and K. Umamaheswari. "Task Scheduling in Distributed Systems Using Heap Intelligent Discrete Particle Swarm Optimization." Computational Intelligence 33.4 (2017): 737-770. Crossref. Web.

Tragos, Elias Z. et al. "Spectrum Assignment in Cognitive Radio Networks: A Comprehensive Survey." IEEE Communications Surveys & Tutorials 15.3 (2013): 1108-1135. Crossref. Web.

Yonghong Zeng, and Ying-chang Liang. "Eigenvalue-Based Spectrum Sensing Algorithms for Cognitive Radio." IEEE Transactions on Communications 57.6 (2009): 1784-1793. Crossref. Web.

Yucek, Tevfik, and Huseyin Arslan. "A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications." IEEE Communications Surveys & Tutorials 11.1 (2009): 116-130. Crossref. Web.


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present

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