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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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 HIGH-IMPACT PAPER 

Performance Comparison of the Differential Evolution and Particle Swarm Optimization Algorithms in Free-Space Optical Communications Systems

BASGUMUS, A. See more information about BASGUMUS, A. on SCOPUS See more information about BASGUMUS, A. on IEEExplore See more information about BASGUMUS, A. on Web of Science, NAMDAR, M. See more information about  NAMDAR, M. on SCOPUS See more information about  NAMDAR, M. on SCOPUS See more information about NAMDAR, M. on Web of Science, YILMAZ, G. See more information about  YILMAZ, G. on SCOPUS See more information about  YILMAZ, G. on SCOPUS See more information about YILMAZ, G. on Web of Science, ALTUNCU, A. See more information about ALTUNCU, A. on SCOPUS See more information about ALTUNCU, A. on SCOPUS See more information about ALTUNCU, A. on Web of Science
 
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Download PDF pdficon (664 KB) | Citation | Downloads: 1,024 | Views: 4,804

Author keywords
communication systems, cooperative systems, distance measurement, evolutionary computation, particle swarm optimization

References keywords
optimization(16), swarm(14), optical(7), evolution(7), communications(7), algorithm(7), space(6), free(6), systems(5), relay(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2015-05-31
Volume 15, Issue 2, Year 2015, On page(s): 17 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.02003
Web of Science Accession Number: 000356808900003
SCOPUS ID: 84979832517

Abstract
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In this comparative study we evaluate the performance of Differential Evolution (DE) and Particle Swarm Optimization (PSO) algorithms in free space optical communications systems. In particular we obtain the optimal transmission distances for different relay nodes in the parallel decode-and-forward relaying schemes by optimizing the relay placements. We analyze that the cost functions are suitably minimized. Then we investigate the execution time and the stability of the DE and PSO algorithms for decode-and-forward relay-assisted free space optical links. The simulation results demonstrate that the PSO algorithm outperforms DE algorithm in terms of the minimization of the cost function. Furthermore the results indicate that we get the similar performance for the execution-time and optimization results in the DE and PSO algorithms.


References | Cited By  «-- Click to see who has cited this paper

[1] M. Safari and M. Uysal, "Relay-assisted free-space optical communication," IEEE Trans. Wireless Commun., vol. 7, no. 12, pp. 5441-5449, Dec. 2008.
[CrossRef] [Web of Science Times Cited 429] [SCOPUS Times Cited 499]


[2] M. Karimi and M. Nasiri-Kenari, "Free space optical communications via optical amplify-and-forward relaying," J. Lightwave Technol., vol. 29, no. 2, pp. 242-248, Jan. 2011.
[CrossRef] [Web of Science Times Cited 95] [SCOPUS Times Cited 118]


[3] M. Karimi and M. Nasiri-Kenari, "BER analysis of cooperative systems in free-space optical networks," J. Lightwave Technol., vol. 27, no. 24, pp. 5639-5647, Dec. 2009.
[CrossRef] [Web of Science Times Cited 74] [SCOPUS Times Cited 87]


[4] M. Karimi and M. Nasiri-Kenari, "Outage analysis of relay-assisted free space optical communications," IET Commun., vol. 4, no. 12, pp. 1423-1432, Aug. 2010.
[CrossRef] [Web of Science Times Cited 55] [SCOPUS Times Cited 71]


[5] M.A. Kashani and M. Uysal, "Outage performance and diversity gain analysis of free-space optical multi-hop parallel relaying," J. Opt. Commun. Netw., vol. 5, no. 8, pp. 901-909, Aug. 2013.
[CrossRef] [Web of Science Times Cited 61] [SCOPUS Times Cited 64]


[6] M.A. Kashani, M. Safari and M. Uysal, "Optimal relay placement and diversity analysis of relay- assisted free-space optical communications systems," J. Opt. Commun. Netw., vol. 5, no. 1, pp. 37-47, Jan. 2013.
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[7] C. Knievel, and P. A. Hoeher, "On Particle Swarm Optimization for MIMO Channel Estimation," Journal of Electrical and Computer Engineering, vol. 2012, doi:10.1155/2012/614384, 10pp., Dec. 2011.
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[8] L. Su, P. Wang, and F. Liu, "Particle swarm optimization based resource block allocation algorithm for downlink LTE systems," IEEE 18th Asia-Pacific Conference on Communications, pp. 970-974, Jeju Island, Oct. 2012.
[CrossRef] [SCOPUS Times Cited 25]


[9] F. R. Dunand, and T. Abrao, "Energy-Efficient Power Allocation for WDM/OCDM Networks With Particle Swarm Optimization," J. Opt. Commun. Netw., vol. 5, no. 5, pp. 512-523, May 2013.
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[12] L. Xiang, L. Ximing, M. F. Ercan, and Z. Yi, "A New Hybrid Algorithm Based on Collaborative Line Search and Particle Swarm Optimization," IEEE 4th International Conference on Autonomous Robots and Agents, pp. 486-489, Wellington, Feb. 2009.
[CrossRef] [SCOPUS Times Cited 2]


[13] R. Storn, and K. Price, "Differential evolution: A Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces," Technical report, TR-95-012, International Computer Science Institute, Germany, Mar. 1995

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[15] M. Zhang, W. Zhangi, and Y. Sun, "Chaotic Co-evolutionary Algorithm Based on Differential Evolution and Particle Swarm Optimization," IEEE International Conference on Automation and Logistics, pp. 885-889, Shenyang, Aug. 2009.
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[16] I. Ahmed, S. Sadeque, and S. Pervin, "Margin Adaptive Resource Allocation for Multiuser OFDM Systems by Modified Particle Swarm Optimization and Differential Evolution," IEEE 21st International Conference on Electrical Communications and Computers, pp. 227-231, San Andres Cholula, Mar. 2011.
[CrossRef] [SCOPUS Times Cited 8]


[17] J. Zhang, S. Chen, X. Mu, and L. Hanzo,"Evolutionary-Algorithm-Assisted Joint Channel Estimation and Turbo Multiuser Detection/Decoding for OFDM/SDMA," IEEE Transactions on Vehicular Technology, vol. 63, no. 3, pp. 1204-1222, Mar. 2014.
[CrossRef] [Web of Science Times Cited 43] [SCOPUS Times Cited 48]


[18] X. Xu, and Y. Li, "Comparison between Particle Swarm Optimization, Differential Evolution and Multi-parents Crossover," IEEE International Conference on Computational Intelligence and Security, pp. 124-127, Harbin, Dec. 2007.
[CrossRef] [Web of Science Times Cited 26] [SCOPUS Times Cited 1]


[19] S. K. Goudos, Z. D. Zaharis, K. B. Baltzis, C. L. Hilas and, J. N. Sahalos, "A Comparative Study of Particle Swarm Optimization and Differential Evolution on Radar Absorbing Materials Design for EMC Applications," IEEE International Symposium on Electromagnetic Compatibility, pp. 1-4, Athens, Jun. 2009.
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[20] B. Basu, and G. K. Mahanti, "A Comparative Study of Modified Particle Swarm Optimization, Differential Evolution and Artificial Bees Colony Optimization in Synthesis of Circular Array," IEEE International Conference on Power, Control and Embedded Systems, pp. 1-5, Allahabad, Dec. 2010.
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[21] V. Roberge, M. Tarbouchi, and G. Labonte, "Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-Time UAV Path Planning," IEEE Transactions on Industrial Infirmatics, vol. 9, no. 1, pp. 132-141. Feb. 2013.
[CrossRef] [Web of Science Times Cited 650] [SCOPUS Times Cited 821]


[22] A. Deb, J. S. Roy, and B. Gupta, "Performance Comparison of Differential Evolution, Particle Swarm Optimization and Genetic Algorithm in the Design of Circularly Polarized Microstrip Antennas," IEEE Transactions on Antennas and Propagation, vol. 62, no. 8, pp. 3920-3928, May. 2014.
[CrossRef] [Web of Science Times Cited 89] [SCOPUS Times Cited 105]


[23] A.S. Avestimehr, D.N.C. Tse, "Outage-optimal relaying in the low SNR regime," Proceedings of the IEEE International Symposium on Information Theory, pp. 941-45, Adelaide, SA, 2005.
[CrossRef] [SCOPUS Times Cited 19]




References Weight

Web of Science® Citations for all references: 33,514 TCR
SCOPUS® Citations for all references: 2,109 TCR

Web of Science® Average Citations per reference: 1,396 ACR
SCOPUS® Average Citations per reference: 88 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-06-07 08:43 in 148 seconds.




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