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Comparison of Hybrid Firefly Algorithms for Power Allocation in a TV White Space Network

by Kennedy K. Ronoh, George Kamucha, Tonny K. Omwansa
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 38
Year of Publication: 2019
Authors: Kennedy K. Ronoh, George Kamucha, Tonny K. Omwansa
10.5120/ijca2019919264

Kennedy K. Ronoh, George Kamucha, Tonny K. Omwansa . Comparison of Hybrid Firefly Algorithms for Power Allocation in a TV White Space Network. International Journal of Computer Applications. 178, 38 ( Aug 2019), 37-43. DOI=10.5120/ijca2019919264

@article{ 10.5120/ijca2019919264,
author = { Kennedy K. Ronoh, George Kamucha, Tonny K. Omwansa },
title = { Comparison of Hybrid Firefly Algorithms for Power Allocation in a TV White Space Network },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2019 },
volume = { 178 },
number = { 38 },
month = { Aug },
year = { 2019 },
issn = { 0975-8887 },
pages = { 37-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number38/30789-2019919264/ },
doi = { 10.5120/ijca2019919264 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:52:33.728423+05:30
%A Kennedy K. Ronoh
%A George Kamucha
%A Tonny K. Omwansa
%T Comparison of Hybrid Firefly Algorithms for Power Allocation in a TV White Space Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 38
%P 37-43
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

TV white spaces (TVWS) can be used by Secondary Users (SUs) through Dynamic Spectrum Access (DSA) as long as they do not cause harmful interference to Primary Users (PUs). Due spectrum scarcity, there is increasing demand for DSA. When there is a high density of SUs in a TVWS network such as cellular access to TVWS, problem of interference among SUs will arise. Possibility of harmful interference to PUs may also arise. Optimization of power allocation is therefore necessary to reduce the level of interference among SUs and to protect PUs against harmful interference. Performance of different hybrid firefly algorithm with particle swarm optimization and genetic algorithm for optimization of power allocation in a TVWS network are compared. Simulation was done using Matlab. Simulation results show that hybrid of firefly algorithm, particle swarm optimization and genetic algorithm outperform other hybrid firefly algorithms. Hybrid of firefly algorithm, particle swarm optimization and genetic algorithm achieves best throughput, sum power as well as objective function value.

References
  1. K. Patil, R. Prasad, and K. Skouby, “A survey of worldwide spectrum occupancy measurement campaigns for cognitive radio,” in Devices and Communications (ICDeCom), 2011 International Conference on, 2011, pp. 1–5.
  2. M. Mehdawi, N. Riley, K. Paulson, A. Fanan, and M. Ammar, “Spectrum occupancy survey in HULL-UK for cognitive radio applications: measurement & analysis,” Int. J. Sci. Technol. Res., vol. 2, no. 4, pp. 231–236, 2013.
  3. M. Nekovee, T. Irnich, and J. Karlsson, “Worldwide trends in regulation of secondary access to white spaces using cognitive radio,” Wirel. Commun. IEEE, vol. 19, no. 4, pp. 32–40, 2012.
  4. M. Fadda, V. Popescu, M. Murroni, P. Angueira, and J. Morgade, “On the Feasibility of Unlicensed Communications in the TV White Space: Field Measurements in the UHF Band,” Int. J. Digit. Multimed. Broadcast., vol. 2015, pp. 1–8, 2015.
  5. J. Heo, G. Noh, S. Park, S. Lim, E. Kim, and D. Hong, “Mobile TV White Space with Multi-Region Based Mobility Procedure,” IEEE Wirel. Commun. Lett., vol. 1, no. 6, pp. 569–572, Dec. 2012.
  6. M. Nekovee, “A Survey of Cognitive Radio Access to TV White Spaces,” Int. J. Digit. Multimed. Broadcast., vol. 2010, pp. 1–11, 2010.
  7. R. Kennedy, K. George, O.-O. William, O. Thomas, and O. Tonny, “Firefly algorithm based power control in wireless TV white space network,” in AFRICON, 2017 IEEE, 2017, pp. 155–160.
  8. X.-S. Yang, “Firefly algorithms for multimodal optimization,” in International Symposium on Stochastic Algorithms, 2009, pp. 169–178.
  9. S. Arora and S. Singh, “A conceptual comparison of firefly algorithm, bat algorithm and cuckoo search,” in 2013 International Conference on Control, Computing, Communication and Materials (ICCCCM), Allahabad, India, 2013, pp. 1–4.
  10. K. Ronoh, G. Kamucha, T. Olwal, and T. Omwansa, “Improved Resource Allocation for TV White Space Network Based on Modified Firefly Algorithm,” J. Comput. Inf. Technol., vol. 26, no. 3, pp. 167–167, Sep. 2018.
  11. S. Y. Lee, M. K. Kwon, and S. H. Lee, “Transmit power control scheme for TV white space wireless system,” in Advanced Communication Technology (ICACT), 2011 13th International Conference on, 2011, pp. 1025–1029.
  12. Z. Xue, “Geolocation Spectrum Database Assisted Coexistence of Multiple Device-to-device in TV White Space,” J. Inf. Comput. Sci., vol. 12, no. 11, pp. 4443–4456, Jul. 2015.
  13. H. R. Karimi, “Geolocation databases for white space devices in the UHF TV bands: Specification of maximum permitted emission levels,” in New Frontiers in Dynamic Spectrum Access Networks (DySPAN), 2011 IEEE Symposium on, 2011, pp. 443–454.
  14. Z. Xue, L. Shen, G. Ding, Q. Wu, L. Zhang, and Q. Wang, “Coexistence among Device-to-Device communications in TV white space based on geolocation database,” in High Mobility Wireless Communications (HMWC), 2014 International Workshop on, 2014, pp. 17–22.
  15. S. Arunachalam, T. AgnesBhomila, and M. Ramesh Babu, “Hybrid Particle Swarm Optimization Algorithm and Firefly Algorithm Based Combined Economic and Emission Dispatch Including Valve Point Effect,” in Swarm, Evolutionary, and Memetic Computing, vol. 8947, B. K. Panigrahi, P. N. Suganthan, and S. Das, Eds. Cham: Springer International Publishing, 2015, pp. 647–660.
  16. P. Kora and K. S. Rama Krishna, “Hybrid firefly and Particle Swarm Optimization algorithm for the detection of Bundle Branch Block,” Int. J. Cardiovasc. Acad., vol. 2, no. 1, pp. 44–48, Mar. 2016.
  17. I. Fister, I. Fister, X.-S. Yang, and J. Brest, “A comprehensive review of firefly algorithms,” Swarm Evol. Comput., vol. 13, pp. 34–46, Dec. 2013.
  18. J. Luthra and S. K. Pal, “A hybrid Firefly Algorithm using genetic operators for the cryptanalysis of a monoalphabetic substitution cipher,” in 2011 World Congress on Information and Communication Technologies, Mumbai, India, 2011, pp. 202–206.
  19. R. Kennedy, O. Tonny, and K. George, “Novel Resource Allocation Algorithm for TV White Space Networks Using Hybrid Firefly Algorithm,” Int. J. Comput., vol. 32, no. 1, p. 20, 2019.
  20. National Institute of Technology, Warangal, India, B. V. Kumar, N. V. Srikanth, and Associate Professor, Department of Electrical Engineering, National In stitute of Technology, Warangal, India, “Bat Algorithm a nd Firefly Algorithm f or Improving Dynamic Stability o f Power Systems Using UPFC,” Int. J. Electr. Eng. Inform., vol. 8, no. 1, pp. 164–188, Mar. 2016.
  21. M. Elkhechafi, H. Hachimi, and Y. Elkettani, “A new hybrid cuckoo search and firefly optimization,” Monte Carlo Methods Appl., vol. 24, no. 1, pp. 71–77, Mar. 2018.
  22. A. Layeb and Z. Benayad, “A Novel Firefly Algorithm Based Ant Colony Optimization For Solving Combinatorial Optimization ProblemS,” Int. J. Comput. Sci. Appl., vol. 11, no. 2, p. 19, 2014.
  23. D. Gurney, G. Buchwald, L. Ecklund, S. Kuffner, and J. Grosspietsch, “Geo-location database techniques for incumbent protection in the TV white space,” in New Frontiers in Dynamic Spectrum Access Networks, 2008. DySPAN 2008. 3rd IEEE Symposium on, 2008, pp. 1–9.
  24. O. Katircioglu, H. Isel, O. Ceylan, F. Taraktas, and H. B. Yagci, “Comparing ray tracing, free space path loss and logarithmic distance path loss models in success of indoor localization with RSSI,” in 2011 19thTelecommunications Forum (TELFOR) Proceedings of Papers, Belgrade, Serbia, 2011, pp. 313–316.
Index Terms

Computer Science
Information Sciences

Keywords

TV White Spaces power allocation cognitive radio hybrid firefly algorithm continuous optimization firefly algorithm genetic algorithm particle swarm optimization.

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