KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Relay Selection Scheme Based on Quantum Differential Evolution Algorithm in Relay Networks

  • Gao, Hongyuan (College of Information and communication Engineering, Harbin Engineering University) ;
  • Zhang, Shibo (College of Information and communication Engineering, Harbin Engineering University) ;
  • Du, Yanan (College of Information and communication Engineering, Harbin Engineering University) ;
  • Wang, Yu (College of Information and communication Engineering, Harbin Engineering University) ;
  • Diao, Ming (College of Information and communication Engineering, Harbin Engineering University)
  • Received : 2017.01.08
  • Accepted : 2017.04.17
  • Published : 2017.07.31
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Abstract

It is a classical integer optimization difficulty to design an optimal selection scheme in cooperative relay networks considering co-channel interference (CCI). In this paper, we solve single-objective and multi-objective relay selection problem. For the single-objective relay selection problem, in order to attain optimal system performance of cooperative relay network, a novel quantum differential evolutionary algorithm (QDEA) is proposed to resolve the optimization difficulty of optimal relay selection, and the proposed optimal relay selection scheme is called as optimal relay selection based on quantum differential evolutionary algorithm (QDEA). The proposed QDEA combines the advantages of quantum computing theory and differential evolutionary algorithm (DEA) to improve exploring and exploiting potency of DEA. So QDEA has the capability to find the optimal relay selection scheme in cooperative relay networks. For the multi-objective relay selection problem, we propose a novel non-dominated sorting quantum differential evolutionary algorithm (NSQDEA) to solve the relay selection problem which considers two objectives. Simulation results indicate that the proposed relay selection scheme based on QDEA is superior to other intelligent relay selection schemes based on differential evolutionary algorithm, artificial bee colony optimization and quantum bee colony optimization in terms of convergence speed and accuracy for the single-objective relay selection problem. Meanwhile, the simulation results also show that the proposed relay selection scheme based on NSQDEA has a good performance on multi-objective relay selection.

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References

  1. A. Nosratinia, T. E. Hunter and A. Hedayat, "Cooperative communication in wireless networks," IEEE Communications Magazine, vol. 42, no. 10, pp. 74-80, Oct., 2004. https://doi.org/10.1109/MCOM.2004.1341264
  2. X. Xu, L. Li and et al, "Energy-efficient buffer-aided optimal relay selection scheme with power adaptation and inter-relay interference cancellation," KSII Transactions on Internet and Information Systems, vol 10, no. 11, pp. 5343-5364, Nov., 2016. https://doi.org/10.3837/tiis.2016.11.008
  3. W. Guo, J. Zhang and et al, "An amplify-and-forward relaying scheme based on network coding for deep space communication," KSII Transactions on Internet and Information Systems, vol. 10, no. 2, pp. 670-683, Feb., 2016. https://doi.org/10.3837/tiis.2016.02.013
  4. F. Etezadi, K. Zarifi, A. Ghrayeb and S.Affes, "Decentralized relay selection schemes in uniformly distributed wireless sensor networks," IEEE Transactions on Wireless Communications, vol. 11, no. 3, pp. 938-951, March, 2012. https://doi.org/10.1109/TWC.2012.010312.101314
  5. X. Lin and L. Cuthbert, "Load based relay selection algorithm for fairness in relay based OFDMA cellular systems," in Proc. of IEEE Wireless Communications and Networking Conference (WCNC), pp. 1-6, April 5-8, 2009.
  6. J. Cao, T. Zhang and et al, "Multi-relay selection schemes based on evolutionary algorithm in cooperative relay networks," International Journal of Communication Systems, vol. 27, no. 4, pp. 571-591, Dec., 2013. https://doi.org/10.1002/dac.2710
  7. Y. Jing and H. Jafarkhani, "Single and multiple relay selection schemes and their achievable diversity orders," IEEE Transactions on Wireless Communications, vol. 8, no. 3, pp. 1414-1423, March, 2009. https://doi.org/10.1109/TWC.2008.080109
  8. D. S. Michalopoulos and G. K. Karagiannidis, "Performance analysis of single relay selection in rayleigh fading," IEEE Transactions on Wireless Communications, vol. 7, no. 10, pp. 3718-3724, Oct., 2008. https://doi.org/10.1109/T-WC.2008.070492
  9. T. C. y. Ng and W. Yu, "Joint optimization of relay strategies and resource allocations in cooperative cellular networks," IEEE Journal on Selected Areas in Communications, vol. 25, no. 2, pp. 328-339, Feb., 2007. https://doi.org/10.1109/JSAC.2007.070209
  10. C. Esli and A. Wittneben, "A hierarchical AF protocol for distributed orthogonalization in multiuser relay networks," IEEE Transactions on Vehicular Technology, vol. 59, no. 8, pp. 3902-3916, Oct., 2010. https://doi.org/10.1109/TVT.2010.2064344
  11. S. Sharma, Y. Shi, Y. T. Hou and S. Kompella, "An optimal algorithm for relay node assignment in cooperative Ad Hoc networks," IEEE/ACM Transactions on Networking, vol. 19, no. 3, pp. 879-892, June, 2011. https://doi.org/10.1109/TNET.2010.2091148
  12. S. Atapattu, Y. Jing, H. Jiang and C. Tellambura, "Relay selection and performance analysis in multiple-user networks," IEEE Journal on Selected Areas in Communications, vol. 31, no. 8, pp. 1-13, Oct., 2013. https://doi.org/10.1109/JSAC.2013.SUP.0513000
  13. J. Xu, S. Zhou and Z. Niu, "Interference-aware relay selection for multiple source-destination cooperative networks," in Proc. of 15th Asia-Pacific Conference on APCC 2009 in Communications, pp. 338-341, Oct., 2009.
  14. D. Karaboga and B. Basturk, "On the performance of artificial bee colony (ABC) algorithm," Applied Soft Computing, vol. 8, no. 1, pp.687-697, Jan., 2008. https://doi.org/10.1016/j.asoc.2007.05.007
  15. H. Gao and C. Li, "Opposition-based quantum firework algorithm for continuous optimisation problems," International Journal of Computing Science and Mathematics,vol. 6, no. 3, pp. 256-265, June, 2015. https://doi.org/10.1504/IJCSM.2015.069747
  16. J. Li and M. Diao, "Quantum bee colony optimization based relay selection scheme in cooperative relay networks," Journal of Computational Information Systems, vol. 11, no. 23, pp. 8489-8499, 2015.
  17. R. Storn and K. Price, "Dieffrential evolution-a simple and effieient heuristic for global optimization over continuous spaces," Jounal of Global Optsmization, vol. 11, no. 4, pp. 341-359, Dec., 1997. https://doi.org/10.1023/A:1008202821328
  18. N. Srinivas and K. Deb, "Mutiobjective optimization using nondominated sorting in genetic algorithms," Evolutionary Computation, vol. 2, no. 3,pp. 221-248, 1994. https://doi.org/10.1162/evco.1994.2.3.221
  19. K. Deb, A. Pratap and et al, "A fast and elitist multiobjective genetic algorithm: NSGA-II," IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182-197, April, 2002. https://doi.org/10.1109/4235.996017
  20. E. Zitzler and L. Thiele, "Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach," IEEE Transactions on Evolutionary Computation, vol. 3, no. 4, pp. 257-271, Nov., 1999. https://doi.org/10.1109/4235.797969
  21. E. Zitzler, M. Laumanns and L. Thiele, "SPEA2: improving the strength Pareto evolutionary algorithm," in Proc. of evolutionary for design, optimization and control with application to an industrial problems (EUROGEN2001), 2002:pp.95-100.
  22. K. Sindhya, K. Miettinen and K. Deb, "A hybrid framework for evolutionary multi objective optimization," IEEE Transactions on Evolutionary Computation, vol. 17, no. 4, pp. 495-511, Aug., 2013. https://doi.org/10.1109/TEVC.2012.2204403
  23. J. N. Laneman, D. N. C. Tse, and G. W. Wornell, "Cooperative diversity in wireless networks: efficient protocols and outage behavior," Information Theory, IEEE Transactions on, vol. 50, no. 12, pp. 3062-3080, Dec., 2004. https://doi.org/10.1109/TIT.2004.838089
  24. J. Z. LI, M. Diao, " QBCO and NSQBCO based multi-user single-relay selection scheme in cooperative relay networks," International Journal of Signal Processing, Image Processing and Pattern Recognition , vol. 9, no. 7, pp. 407-424, Sept., 2016.

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