Implementation of Cognitive Wireless Sensor Network with Energy Aware Cooperative Spectrum Sensing by Different Censoring Techniques

International Journal of Electronics and Communication Engineering
© 2020 by SSRG - IJECE Journal
Volume 7 Issue 5
Year of Publication : 2020
Authors : D.Narmatha, W.Jenifa, Pushpa Mettilsha
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How to Cite?

D.Narmatha, W.Jenifa, Pushpa Mettilsha, "Implementation of Cognitive Wireless Sensor Network with Energy Aware Cooperative Spectrum Sensing by Different Censoring Techniques," SSRG International Journal of Electronics and Communication Engineering, vol. 7,  no. 5, pp. 24-32, 2020. Crossref, https://doi.org/10.14445/23488549/IJECE-V7I5P105

Abstract:

Energy conservation is needed as the cognitive wireless sensor network's lifetime depends on energy. The cooperative spectrum sensing technique is that remote sensors participate and share their detecting data and send their outcome to the fusion center to improve the detecting execution and exactness. This work aims to lessen vitality utilization in helpful range detecting by different techniques, for example, Knapsack-based Energy Efficient Node Selection Scheme (KEENSS) and censoring and sleeping scheme. KEENSS diminishes the vitality expended for revealing range detecting results to the fusion center. The node selection issue is defined as a backpack issue and to infer its solution by distance calculation and weight allocation. The energy of KEENSS is calculated by considering transmit energy, sensing energy, and the path loss exponent for different environments. A combined censoring and sleeping scheme is proposed where each sensor kills its detecting module with a sleeping rate likelihood at each detecting period on account of the sensor is on, a censoring policy arrangement is utilized to send the decisions to the fusion center. The network energy consumption is limited depending on the detection probability and false alarm derived for AND rule and OR rule and by considering censoring and sleeping rate. The simulation result shows that reduced energy consumption is obtained using a combined censoring and sleeping scheme of 143 nJ and 157 nJ for AND fusion rule and OR fusion rule, respectively, while KEENSS provides energy consumption for five selected nodes 379 nJ and 14 selected nodes is 690 nJ. The simulation result of the report time-saving ratio for OR rule is 0.2207 and for AND rule is 0.3289. The simulation result shows that reduced energy consumption is obtained using combined censoring and sleeping scheme in which AND rule outperforms OR rule for a lower value of probability coefficient as 0.2, and the OR rule outperforms AND rule for a higher value of the probability coefficient as 0.8.

Keywords:

censoring and sleeping rate, Weight allocation, Energy-saving ratio.

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