Cooperative spectrum sensing with adaptive energy threshold control and efficient data fusion

Ling, Xiang; Zhang, Bao; Wen, Hong; Wu, Bin; Xu, Shizhong; Pan, Lili

doi:10.1109/iccchina.2013.6671143

Cited by 1 publication

(1 citation statement)

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“…However, detection performance may be affected by shadowing effect and the hidden terminal problem and SU may not detect the activity of the PU within the short interval of sensing period [5]. Thus, to solve this issue, cooperative spectrum sensing (CSS) was proposed by [6, 7]; it is based on continuing to monitor the spectrum periodically to overcome hidden terminal and shadowing problems for minimizing interference. The well-established local sensing mechanism for spectrum sensing in CR networks is energy detection.…”

Section: Introductionmentioning

confidence: 99%

Recent Efficient Iterative Algorithms on Cognitive Radio Cooperative Spectrum Sensing to Improve Reliability and Performance

Akbari

Reza

Noordin

et al. 2016

International Journal of Distributed Sensor Networks

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In cognitive radio (CR), cooperative spectrum sensing (CSS) has been extensively explored to be accounted for in a spectrum scanning method that permits secondary users (SUs) or cognitive radio users to utilize discovered spectrum holes caused by the absence of primary users (PUs). This paper focuses on optimality of analytical study on the common soft decision fusion (SDF) CSS based on different iterative algorithms which confirm low total probability of error and high probability of detection in detail. In fact, all steps of genetic algorithm (GA), particle swarm optimization (PSO), and imperialistic competitive algorithm (ICA) will be well mentioned in detail and investigated on cognitive radio cooperative spectrum sensing (CRCSS) method. Then, the performance of CRCSS employing GA-, PSO-, and ICA-based scheme is analysed in MATLAB simulation to show superiority of these schemes over other conventional schemes in terms of detection and error performance with very less complexity. In addition, the ICA-based scheme also reveals noticeable convergence and time running performance in comparison to other techniques.

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Section: Introductionmentioning

confidence: 99%