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Finding a Pareto Optimal Solution for a Multi-Objective Problem of Managing Radio Resources in LTE-A Systems: A QoS Aware Algorithm

  • Ayesha Haider AliEmail author
  • Mohsin Nazir
Article
  • 24 Downloads

Abstract

Due to ever increasing users demands, fulfilling the needs of growing users is challenging with constrained resources for Long Term Evolution- Advanced (LTE-A). In this research paper we have proposed an innovative approach for Radio Resource Management (RRM) that makes use of the evolutionary multi-objective optimization techniques for Quality of Service (QoS) facilitation and embeds it with the modern techniques for RRM. We have proposed a novel algorithm that selects an optimal solution out of a set of a representative Pareto front in accordance with the users QoS requirements. It is completely novel as it uses the multi-objective optimization algorithms for achieving desired QoS in LTE-A system. The efficiency and performance of the proposed work has been further improved by autonomously assigning and managing resources among various users and applications. The results have been discussed that showcase efficient system performance and better user experience.

Keywords

QoS Radio resource management Multi-objective optimization Pareto front 

Notes

References

  1. 1.
    Lee, S. B., Pefkianakis, L., Meyerson, A., Xu, S., & Lu, S. (2009). Proportional fair frequency-domain packet scheduling for 3GPP LTE uplink. INFOCOM. IEEE.Google Scholar
  2. 2.
    Mushtaq, S. M., Fowler, S., Mellouk, A., & Augustine, B. (2015). QoE/QoS-aware LTE downlink scheduler for VoIP with power saving. Journal of Network and Computer Applications, 51, 29–46.CrossRefGoogle Scholar
  3. 3.
    Technical Report 25.814, v. 7. (2006). 3GPP Physical layer aspects for evolved UTRA.Google Scholar
  4. 4.
    Ali, A. H., & Nazir, M. (2014). Design considerations for radio resource management of LTE/LTE-A femtocells. Life Science Journal, 6, 68–73.Google Scholar
  5. 5.
    Deb, K. (2001). Multi-objective optimization with evolutionary algorithms (1st ed.). New York: Wiley. ISBN:0-471-87339-X.Google Scholar
  6. 6.
    Antonio, D., Strinati, D., & Calvanese, E. (2010). A radio resource management scheduling algorithm for self-organizing femtocells. Personal, Indoor and mobile radio communications workshops (PIMRC workshops). IEEE.Google Scholar
  7. 7.
    Branke, J., Deb, K., Miettinen, K., & Słowinski, R. (2008). Multi-objective optimization: Interactive and evolutionary approaches. Berlin: Springer. ISBN: 3-540-88907-8.Google Scholar
  8. 8.
    Stefania, S., Issam, T., & Matthew, B. (2009). The UMTS long term evolution forum theory to practice. New York: Willey. ISBN: 978-0-470-69716-0.Google Scholar
  9. 9.
    Gutierrez, I., Bader, F., & Pijoan, J. L. (2008). Prioritization function for packet scheduling in OFDMA systems. Wireless Internet Conference. Google Scholar
  10. 10.
    Wang, A., Xio, L., Zhou, S., Xu, X., & Yao, Y. (2003). Dynamic resource management in the fourth generation wireless systems. In Proceedings of Communication Technology, ICCT. Google Scholar
  11. 11.
    3GPP TSG-RAN TS, 3. (2009). Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access network (E-UTRANN). Google Scholar
  12. 12.
    Assaad, M., & Mourad, A. (2008). New frequency-time scheduling algorithms for 3GPP/LTE-like OFDMA air interface in the downlink. In IEEE Vehicular Technology Conference (VTC). Google Scholar
  13. 13.
    Dahlman, E., Parkvall, S., Skold, J., & Bening, P. (2008). 3G evolution; HSPA and LTE mobile broadband (2nd ed.). Amsterdam: Elsevier.Google Scholar
  14. 14.
    Sandrasegaran, K., Adibah, H., Ramli, M., & Basukala, R. (2010). Delay-prioritized scheduling (DPS) for real time traffic in 3GPP LTE system. In IEEE WCNC. Google Scholar
  15. 15.
    Jani, P., Niko, K., Tero, H., Martti, M., & Mika, R. (2008). Mixed traffic packet scheduling in UTRAN long term evaluation downlink. In International symposium on personal, indoor and mobile radio communications (PIMRC). IEEE.Google Scholar
  16. 16.
    Sandrasegaran, K., Adibah, H., Ramli, M., & Basukala, R. (2010). Delay-prioritized scheduling (DPS) for real time traffic in 3GPP LTE system. In WCNC. IEEE.Google Scholar
  17. 17.
    Machwe, A., Parmee, I., & Miles, J. (2006). Multi-objective analysis of a component based representation within an interactive evolutionary design system. In Proceedings of the 7th international conference in adaptive computing and design and manufacturing. Google Scholar
  18. 18.
    Moety, F., Lahoud, S., Cousin, B., & Khawam, K. (2015). A heuristic algorithm for joint power-delay minimization in green wireless access networks. In International conference on computing, networking and communications (ICNC). Anahiem.Google Scholar
  19. 19.
    Tan, K., Lee, T., Khoo, D., & Khor, E. (2001). A multi-objective evolutionary algorithm toolbox for computer-aided multi-objective optimization. IEEE Transactions on Systems, Man and Cybernetics—Part B: Cybernetics, 31, 537–556.CrossRefGoogle Scholar
  20. 20.
    Fonseca, C., & Fleming, P. (1998). Multi-objective optimization and multiple constraint handling with evolutionary algorithms. IEEE Transactions on Systems, Man, and Cybernetics: Part A: Systems and Humans, 28, 26–37.CrossRefGoogle Scholar
  21. 21.
    Shen, J., Yi, N., Liu, A., & Xiang, H. (2009). Opportunistic scheduling for heterogeneous services in downlink OFDMA system. In International conference on communications and mobile computing, computer society. IEEE.Google Scholar
  22. 22.
    Piro, G., Grieco, L. A., Boggia, G., Capozzi, F., & Camarda, P. (2011). Simulating LTE cellular systems: An open source framework. IEEE Transactions on Vehicular Technology IEEE, 60, 498–513.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceLahore College for Women UniversityLahorePakistan

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