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

10.14445/23488549/IJECE-V7I5P105

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.

References:

[1] Hock Guan Goh, Kae Hsiang Kwong, and Ivan AndonovicandSoung-YueLiew, "The implementation of the cognitive wireless Sensor network using rule-based and supervised approaches" in IEEE International Conference on Frontiers of Communications, Networks and Applications, November 2014, pp. 1-6
[2] Md. AlimulHaque, Md. Faizanuddin, N. K. Singh, "A Study of Cognitive Wireless Sensor Networks: Taxonomy of Attacks and Countermeasures" in World Applied Programming, Vol (2), Issue (11), November 2012. 477-484, ISSN: 2222-2510.
[3] Gayathri Vijay, Elyes Ben Ali Bdiraand Mohamed Ibnkahla, "Cognition in Wireless Sensor Networks: A Perspective," IEEE Sensors Journal, Vol. 11, No. 3, March 2011.
[4] S. Men, Y. Zhou, X. Sun, and Z. Zhou, "A Cooperative Spectrum Sensing Scheme in Wireless Cognitive Sensor Network," Proceedings of the IET International Conference on Communication Technology and Application (ICCTA), 2011, pp. 577-581.
[5] Amir SepasiZahmati, SattarHussain, Xavier Fernando, Ali Grami, "Cognitive Wireless Sensor networks: Emerging Topics and Recent Challenges," IEEE Toronto International Conference, 2009
[6] Andreas Willig, "Recent and Emerging Topics in Wireless Industrial Communications: A Selection," IEEE Transactions on Industrial Informatics, vol. 4, no. 2, May 2008.
[7] Maryam Monemian, Mehdi Mahdavi, and Mohammad JavadOmidi, "Optimum Sensor Selection Based on Energy Constraints in Cooperative Spectrum Sensing for Cognitive Radio Sensor Networks" IEEE sensors journal, vol. 16, no. 6, March 15, 2016.
[8] D. Mercedes, M. Plata, and A. G. A. Reatiga, "Evaluation of energy detection for spectrum sensing based on the dynamic selection of detection threshold," Elsevier Procedia Engineering, International Meeting of Electrical Engineering Research 2012.Volume 35, 2012, pp. 135–143.
[9] Nan Zhaot, F. Richard Yu, Hongjian Sun, and ArumugamNallanathan, "An Energy-Efficient Cooperative Spectrum Sensing Scheme for Cognitive Radio Networks," IEEE Global Communications Conference (GLOBECOM), December 2012, pp.3600 - 3604, ISSN: 1930-529X.
[10] S. Maleki, A. Pandharipande, and G. Leus, "Energy-efficient distributed spectrum sensing for cognitive sensor networks," IEEE Sensors Journal., vol. 11, no. 3, pp. 565–573, Mar. 2011.
[11] SamanAtapattu, ChinthaTellambura, Hai Jiang, "Energy Detection Based Cooperative Spectrum Sensing in Cognitive Radio Networks" in IEEE Transactions on wireless communication, vol. 10, No. 4, April 2011.
[12] T. Yucek and H. Arslan, "A survey of spectrum sensing algorithms for cognitive radio applications," IEEE communications surveys & tutorials, vol. 11, no. 1, first quarter 2009vol. 11, no. 1, pp. 116–130, 2009.
[13] W. Zhang, R. K. Mallik, and K. B. Letaief, "Cooperative spectrum sensing optimization in cognitive radio networks," IEEE Transactions on Wireless Communication, vol. 8, no. 12, pp. 5761–5766, Dec. 2009.
[14] A. Ghasemi and S. Sousa, "Spectrum sensing in cognitive radio networks: Requirements, challenges, and design trade-offs," IEEE Communication Magazine, vol. 46, no. 4, pp. 32–39, Apr. 2008.14]NavdeepKaurKapoor, ShikhareshMajumdar, and BiswajitNandy, "Techniques for Allocation of Sensors in Shared Wireless Sensor Networks," Journal of Networks, vol. 10, no. 1, January 2015.
[15] N.u. Hasan, W. Ejaz, S. Lee, H.S. Kim, "Knapsack-based energy-efficient node selection scheme for cooperative spectrum sensing in cognitive radio sensor networks" IET Communications, 2012, Volume:6, Issue: 17, pp.2998 – 3005, ISSN:1751-8628.
[16] Zaheer Khan, JanneLehtomäki, Kenta Umebayashi, and Johanna Vartiainen, "On the Selection of the Best Detection Performance Sensors for Cognitive Radio Networks" IEEE signal processing letters, vol. 17, no. 4, April 2010.
[17] Manish Arora M. Syamala Devi, "Weight Based Funds Allocation Algorithm," IEEE International Advance Computing Conference, March 2009, pp. 413 – 417.
[18] Edward Peh and Ying-Chang Liang, "Optimization for Cooperative Sensing in Cognitive Radio Networks," IEEE wireless communications and networking conference, 2007, pp. 27-32, ISSN: 1525 -3511.
[19] SinaMaleki, Geert Leus, SymeonChatzinotas, and Bjorn Ottersten, "To AND or To OR: ON Energy-Efficient Distributed Spectrum Sensing with Combined Censoring and Sleeping" IEEE transactions on wireless communications, vol. 14, no. 8, August 2015.
[20] S. Maleki, S.P. Chepuri and G.Leus, "Optimization of hard fusion-based spectrum sensing for energy-constrained cognitive radio networks," Physical communication, vol.9, pp. 193-198, December 2013.
[21] Yunfei Chen, Josef A. Nossek, Amine Mezghani, "Circuit Aware Cognitive Radios for Energy-Efficient Communications" IEEE wireless communications letters, vol.2, no.3, June 2013.
[22] Geert Leus, Rocio Arroyo Valles, SinaMaleki, "Energy-Efficient Spectrum Sensing for Cognitive Sensor Networks," IEEE Workshop on Signal Processing Advances in Wireless Communications, June 2013, pp. 155-159, ISSN: 1948-3244.
[23] Stephen Wang, Yue Wang, Justin P. Coon, and Angela Doufexi, "Energy-efficient Spectrum Sensing and Access for Cognitive Radio Networks," IEEE transactions on vehicular technology, vol.61, no.2, February 2012.
[24] WeixiaZou, Wenshuo Zhang, Zheng Zhou, Xiaojun Huang, "Chain Based OR Rule Cooperative Spectrum Sensing Scheme in Cognitive Sensing Networks "IEEE international symposium on communications and information technologies, October 2010, pp. 1191-1195.
[25] AshishPandharipande, SinaMaleki, and Geert Leus, "Energy-efficient spectrum sensing for cognitive sensor networks", IEEE conference on Industrial Electronics, November 2009, pp.2642 - 2646, ISSN: 1553-572X.
[26] G.Prema, D.Narmatha, "Performance of energy aware cooperative spectrum sensing algorithms in cognitive wireless sensor network" International conference on Green engineering and Technologies, 2016 IEEE.
[27] A. Maizate, S. Aouad "EECDC: An energy Efficient and Coverage-Aware Distributed Clustering Protocol for Wireless Sensor Networks" International Journal of Engineering Trends and Technology 62.1 (2018): 10-14.