AUGMENTATION THE LIFETIME OF THE OPTIMAL COOPERATIVE SPECTRUM SENSING SENSOR NETWORK

Published 31 JAN 2020 •  vol 134  • 


Authors:

 

Hayder S. Rashid Hujijo, 2Department of Communication Techniques Engineering, Engineering Technical College/Najaf, Al-Furat Al-Awsat Technical University, Najaf, Iraq
Mohammed J. Alhasan, 2Department of Communication Techniques Engineering, Engineering Technical College/Najaf, Al-Furat Al-Awsat Technical University, Najaf, Iraq

Abstract:

 

In a sensor-aided cognitive radio network, collaborating battery-powered sensors are deployed to aid the network in cooperative spectrum sensing. These sensors consume energy for spectrum sensing and therefore deplete their lifetime. Therefore, a study is required to minimize the sensing energy consumed and maximize the lifetime, in order to satisfy a larger spectrum utilization. However, this study focused on the spectrum sensing as a major factor at each cognitive radio network. A new cooperative sensing scheme established on the energy detection of each individual sensor was proposed and evaluated in this work by mean of limitation the energy of the wireless sensor elements. The main goals behind the new design are to minimize the sensing energy of each sensor and accurately select appropriate participant sensors in each cooperative sensing operation process. Lastly, the numerical results show that according to the unprecedented mathematical model, which proposed in this study, the lifetime of the cognitive network is increased, as well as, the application of available spectrum by secondary devices become more efficient compared with the existing algorithms. In general, this modification leads to improve the target detection performance.

Keywords:

 

Wireless sensor networks, Cognitive radio, Spectrum sensing, Lifetime, Average sensing energy

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Citations:

 

APA:
Rao, K. K., Kumari, G. L. & Surekha, Y. (2020). Heartbeat Classification using the Recurrent Neural Network based on the Developed Spider Monkey-Bird Swarm Optimization Algorithm- Proposed Method. International Journal of Advanced Science and Technology (IJAST), ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, 134, 1-8. doi: 10.33832/ijast.2020.134.01.

MLA:
Rao, K. K., et al. “Heartbeat Classification using the Recurrent Neural Network based on the Developed Spider Monkey-Bird Swarm Optimization Algorithm- Proposed Method.” International Journal of Advanced Science and Technology, ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, vol. 134, 2020, pp. 1-10. IJAST, http://article.nadiapub.com/IJAST/Vol134/1.html.

IEEE:
[1] K. Koteswara Rao, G. Lalitha Kumari, and Y. Surekha, “Heartbeat Classification using the Recurrent Neural Network based on the Developed Spider Monkey-Bird Swarm Optimization Algorithm- Proposed Method.” International Journal of Advanced Science and Technology (IJAST), ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, vol. 134, pp. 1-8, Jan 2020.