Energy efficient spectrum sensing for cognitive radio network using artificial bee colony algorithm

  • Authors

    • Geoffrey Eappen VIT VELLORE
    • Dr T. Shankar
    2018-09-17
    https://doi.org/10.14419/ijet.v7i4.10094
  • Cognitive Radio Network, Artificial Bee colony, Particle Swarm Optimization, Energy Efficiency.

  • In this paper Artificial Bee Colony (ABC) algorithm based optimization of energy efficiency for spectrum sensing in a Cognitive Radio Network (CRN) is implemented. ABC algorithm which is an efficient optimization technique is used for optimizing energy efficiency func-tion derived for cognitive users, where energy efficiency function is derived as the dependency on spectrum sensing time and the transmis-sion power. Energy efficiency optimized by ABC is compared with Particle Swarm Optimization (PSO) based technique. Simulation results shows that with ABC it is able to achieve more energy efficient spectrum sensing as compared to PSO optimized with a margin of 33% efficiency over PSO.

     

     

  • References

    1. [1] Kennedy, R. J. and Eberhart, “Particle swarm optimization." In Proceedings of IEEE International Conference on Neural Networks IV, pages, vol. 1000. 1995.

      [2] Shi, Yuhui, and Russell Eberhart. "A modified particle swarm optimizer." In Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Conference on, pp. 69-73. IEEE, 1998. https://doi.org/10.1109/ICEC.1998.699146.

      [3] Angeline, Peter J. "Evolutionary optimization versus particle swarm optimization: Philosophy and performance differences." In International Conference on Evolutionary Programming, pp. 601-610. Springer, Berlin, Heidelberg, 1998. https://doi.org/10.1007/BFb0040811.

      [4] Mitola, Joseph, and Gerald Q. Maguire. "Cognitive radio: making software radios more personal." IEEE personal communications 6, no. 4 (1999): 13-18. https://doi.org/10.1109/98.788210.

      [5] Force, FCC Spectrum Policy Task. "Report of the spectrum efficiency working group." http://www. fcc. Gov/sptf/reports. Html (2002).

      [6] Lovbjerg, Morten, and Thiemo Krink. "Extending particle swarm optimizers with self-organized criticality." In Evolutionary Computation, 2002. CEC'02. Proceedings of the 2002 Congress on, vol. 2, pp. 1588-1593. IEEE, 2002.

      [7] Parsopoulos, Konstantinos E., and Michael N. Vrahatis. "On the computation of all global minimizers through particle swarm optimization." IEEE Transactions on evolutionary computation 8, no. 3 (2004): 211-224. https://doi.org/10.1109/TEVC.2004.826076.

      [8] Van Den Bergh, Frans. "An analysis of particle swarm optimizers." PhD diss., University of Pretoria, 2001.

      [9] Kataria, Amit. "Cognitive radios: spectrum sensing issues." PhD diss., University of Missouri--Columbia, 2007.

      [10] Haykin, Simon, David J. Thomson, and Jeffrey H. Reed. "Spectrum sensing for cognitive radio." Proceedings of the IEEE 97, no. 5 (2009): 849-877. https://doi.org/10.1109/JPROC.2009.2015711.

      [11] Blondin, James. "Particle swarm optimization: A tutorial." Availaible from: http: //cs. armstrong. Edu/sad/csci8100/pso tutorial. Pdf (2009).

      [12] Pulikanti, Srikanth, and Alok Singh. "An artificial bee colony algorithm for the quadratic knapsack problem." In International Conference on Neural Information Processing, pp. 196-205. Springer, Berlin, Heidelberg, 2009. https://doi.org/10.1007/978-3-642-10684-2_22.

      [13] Benítez, César Manuel Vargas, and Heitor Silvério Lopes. "Parallel artificial bee colony algorithm approaches for protein structure prediction using the 3dhp-sc model." In Intelligent Distributed Computing IV, pp. 255-264. Springer, Berlin, Heidelberg, 2010.

      [14] Garro, Beatriz A., Humberto Sossa, and Roberto A. Vázquez. "Artificial neural network synthesis by means of artificial bee colony (abc) algorithm." In Evolutionary Computation (CEC), 2011 IEEE Congress on, pp. 331-338. IEEE, 2011. https://doi.org/10.1109/CEC.2011.5949637.

      [15] Li, Guoqiang, Peifeng Niu, and Xingjun Xiao. "Development and investigation of efficient artificial bee colony algorithm for numerical function optimization." Applied soft computing 12, no. 1 (2012): 320-332. https://doi.org/10.1016/j.asoc.2011.08.040.

      [16] Bhongade Sandeep, Geoffrey Eappen, Prof H.O. Gupta,-“Coordination control scheme by SSSC and TCPS with Redox Flow battery for optimized automatic Generation Controlâ€, Proceedings of the IEEE International Conference on Renewable Energy and Sustainable energy sources,ICRESE’13,2013

      [17] Liu, Xin, Min Jia, Xuemai Gu, and Xuezhi Tan. "Optimal periodic cooperative spectrum sensing based on weight fusion in cognitive radio networks." Sensors 13, no. 4 (2013): 5251-5272. https://doi.org/10.3390/s130405251.

      [18] Eappen, Geoffrey, and Sandeep Bhongade. "Optimized automatic generation control scheme including SMES in an inter connected power system." Electrical and Electronic Engineering: An International Journal 2, no. 3 (2013): 29-37.

      [19] Brajevic, Ivona, and Milan Tuba. "An upgraded artificial bee colony (ABC) algorithm for constrained optimization problems." Journal of Intelligent Manufacturing 24, no. 4 (2013): 729-740. https://doi.org/10.1007/s10845-011-0621-6.

      [20] Saleem, Yasir, and Mubashir Husain Rehmani. "Primary radio user activity models for cognitive radio networks: A survey." Journal of Network and Computer Applications 43 (2014): 1-16. https://doi.org/10.1016/j.jnca.2014.04.001.

      [21] Muthiah, A., and R. Rajkumar. "A comparison of artificial bee colony algorithm and genetic algorithm to minimize the make span for job shop scheduling." Procedia Engineering 97 (2014): 1745-1754. https://doi.org/10.1016/j.proeng.2014.12.326.

      [22] Li, Xinbin, Lu Lu, Lei Liu, Guoqiang Li, and Xinping Guan. "Cooperative spectrum sensing based on an efficient adaptive artificial bee colony algorithm." Soft Computing 19, no. 3 (2015): 597-607. https://doi.org/10.1007/s00500-014-1280-2.

      [23] Shengjun, Wen, Xia Juan, GAO Rongxiang, and Wang Dongyun. "Improved artificial bee colony algorithm based optimal navigation path for mobile robot." In Intelligent Control and Automation (WCICA), 2016 12th World Congress on, pp. 2928-2933. IEEE, 2016.

      [24] Shankar T, Shanmugavel S, Rajesh A, “Hybrid HSA and PSO Algorithm for Energy Efficient Cluster Head Selection in Wireless Sensor Networks, Swarm and Evolutionary Computationâ€, Elsevier Publisher, Volume 30, 2016, Pages 1–10, October 2016.

      [25] Alom, Md Zulfikar, Tapan Kumar Godder, Mohammad Nayeem Morshed, and Asmaa Maali. "Enhanced spectrum sensing based on Energy detection in cognitive radio network using adaptive threshold." In Networking, Systems and Security (NSysS), 2017 International Conference on, pp. 138-143. IEEE, 2017. https://doi.org/10.1109/NSysS.2017.7885815.

      [26] Karaboga, Dervis, and Bahriye Basturk. "A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm." Journal of global optimization 39, no. 3 (2007): 459-471. https://doi.org/10.1007/s10898-007-9149-x.

  • Downloads

  • How to Cite

    Eappen, G., & T. Shankar, D. (2018). Energy efficient spectrum sensing for cognitive radio network using artificial bee colony algorithm. International Journal of Engineering & Technology, 7(4), 2319-2324. https://doi.org/10.14419/ijet.v7i4.10094