DOAJ Open Access 2019

Covariance matrix opportunistic cooperative spectrum sensing of high detection probability

Shunlan LIU Jing WANG Jianrong BAO

Abstrak

According to the problem of poor sensing performance caused by the existing spectrum sensing algorithm, the covariance matrix opportunistic cooperative (CMOC) spectrum sensing algorithm was proposed. Based on the traditional covariance matrix spectrum sensing algorithm, odd and even slots were divided by the new proposed algorithm, then opportunistic cooperation was added. The relationship between the false alarm probability and the threshold of the new algorithm was also analyzed, and the analytic detection probability was deduced for the actualization of the more accurate spectrum sensing detection. The simulation results verify that the proposed algorithm obviously improves the detection probability. In Rayleigh fading channel, the detection probability is increased by 0.19 and 0.13, which compared with the existing energy detection spectrum sensing algorithm without relay cooperative and the covariance matrix spectrum sensing algorithm without relay cooperation, when the SNR is −10 dB. Moreover, the proposed algorithm has high energy efficiency as well as the moderate computational complexity, so it is especially suited for the spectrum cognition applications in the new generation wireless communication.

Penulis (3)

S

Shunlan LIU

J

Jing WANG

J

Jianrong BAO

Format Sitasi

LIU, S., WANG, J., BAO, J. (2019). Covariance matrix opportunistic cooperative spectrum sensing of high detection probability. http://www.telecomsci.com/thesisDetails#10.11959/j.issn.1000−0801.2019001

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2019
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DOAJ
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Open Access ✓