Cover
Vol. 18 No. 2 (2022)

Published: December 31, 2022

Pages: 21-32

Original Article

Enhanced Bundle-based Particle Collision Algorithm for Adaptive Resource Optimization Allocation in OFDMA Systems

Haider M. AlSabbagh 1 Mohammed Khalid Ibrahim 2
1Department of Electrical Engineering, College of Engineering, University of Basrah, Basrah, Iraq
2Department of Electrical Engineering, College of Engineering, University of Babylon, Babylon, Iraq
History
  • Received: February 15, 2022
  • Revised: May 2, 2022
  • Accepted: May 4, 2022
  • Available Online: June 5, 2022
DOI

https://doi.org/10.37917/ijeee.18.2.4

Abstract

The necessity for an efficient algorithm for resource allocation is highly urgent because of increased demand for utilizing the available spectrum of the wireless communication systems. This paper proposes an Enhanced Bundle-based Particle Collision Algorithm (EB-PCA) to get the optimal or near optimal values. It applied to the Orthogonal Frequency Division Multiple Access (OFDMA) to evaluate allocations for the power and subcarrier. The analyses take into consideration the power, subcarrier allocations constrain, channel and noise distributions, as well as the distance between user's equipment and the base station. Four main cases are simulated and analyzed under specific operation scenarios to meet the standard specifications of different advanced communication systems. The sum rate results are compared to that achieved with employing another exist algorithm, Bat Pack Algorithm (BPA). The achieved results show that the proposed EB-PAC for OFDMA system is an efficient algorithm in terms of estimating the optimal or near optimal values for both subcarrier and power allocation.

Keywords

References

  1. J. Y. Wu, K. Wu, and M. Wang, “Power-Constrained Quality Optimization for Mobile Video Chatting with Coding-Transmission Adaptation,” IEEE Transactions on Mobile Computing, vol. 20, no. 9, pp. 2862–2876, Sep. 2021.
  2. S. Nosheen and J. Y. Khan, “Quality of Service-and Fairness-Aware Resource Allocation Techniques for IEEE802.11ac WLAN,” IEEE Access, vol. 9, pp. 25579– 25593, 2021.
  3. N. Samarji and M. Salamah, “ERQTM: Energy- Efficient Routing and QoS-Supported Traffic Management Scheme for SDWBANs,” IEEE Sensors Journal, vol. 21, no. 14, pp. 16328–16339, Jul. 2021.
  4. Y. Guo, Z. Qin, Y. Liu, and N. Al-Dhahir, “Intelligent Reflecting Surface Aided Multiple Access over Fading Channels,” IEEE Transactions on Communications, vol. 69, no. 3, pp. 2015–2027, Mar. 2021.
  5. B. Zhai, A. Tang, C. Peng, and X. Wang, “SS- OFDMA: Spatial-Spread Orthogonal Frequency Division Multiple Access for Terahertz Networks,” IEEE Journal on Selected Areas in Communications, vol. 39, no. 6, pp. 1678–1692, Jun. 2021.
  6. N. T. Le, L. N. Tran, Q. D. Vu, and D. Jayalath, “Energy-Efficient Resource Allocation for OFDMA Heterogeneous Networks,” IEEE Transactions on Communications, vol. 67, no. 10, pp. 7043–7057, Oct. 2019.
  7. L. Jiao, H. Yin, and Y. Wu, “Dynamic Resource Allocation for Scalable Video Streaming in OFDMA Wireless Networks,” IEEE Access, vol. 8, pp. 33489– 33499, 2020.
  8. I. Basturk and Y. Chen, “Energy Efficiency for MISO- OFDMA-Based User-Relay Assisted Cellular Networks,” IEEE Systems Journal, vol. 14, no. 4, pp. 5274–5283, Dec. 2020.
  9. M. Condoluci, G. Araniti, A. Molinaro, and A. Iera, “Multicast Resource Allocation Enhanced by Channel State Feedbacks for Multiple Scalable Video Coding Streams in LTE Networks,” IEEE Transactions on Vehicular Technology, vol. 65, no. 5, pp. 2907–2921, May 2016.
  10. J. Y. Kim, T. Kwon, and D. H. Cho, “Resource allocation scheme for minimizing power consumption in OFDM multicast systems,” IEEE Communications Letters, vol. 11, no. 6, pp. 486–488, Jun. 2007.
  11. M. Ibrahim and H. AlSabbagh, “Adaptive OFDMA Resource Allocation using Modified Multi-Dimension Genetic Algorithm,” Iraqi Journal for Electrical and Electronic Engineering, vol. 12, no. 1, pp. 103–113, 2016.
  12. J. Yu, S. Han, and X. Li, “A Robust Game-Based Algorithm for Downlink Joint Resource Allocation in Hierarchical OFDMA Femtocell Network System,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 50, no. 7, pp. 2445–2455, Jul. 2020.
  13. W. F. Sacco and C. R. E. de Oliveira, “A New Stochastic Optimization Algorithm based on a Particle Collision Metaheuristic.” 6th World Congresses of Structural and Multidisciplinary Optimization, Rio de Janeiro, 30 May - 03 June 2005, Brazil.
  14. H. Alves Filho, P. Claudio, W. F. Sacco, and C. M. NA Pereira, Cost-Based Optimization Of A Nuclear Reactor Core Design: a preliminary mode. 2007. [Online]. Available: https://www.researchgate.net/publication/238621160
  15. M. A. Pizani Domiciano, E. H. Shiguemori, L. A. Vieira Dias, and A. M. da Cunha, “Particle collision algorithm applied to automatic estimation of digital elevation model from images captured by UAV,” IEEE Geoscience and Remote Sensing Letters, vol. 15, no. 10, pp. 1630–1634, Oct. 2018.
  16. D. Campos Knupp, A. J. Silva Neto, N. Friburgo, and W. Figueiredo Sacco, “Estimation of Radiative Properties with the Particle Collision Algorithm,” 2007.
  17. S. Bergoch et al., “Automatic configuration for neural network applied to atmospheric temperature profile identification.” EngOpt 2012-International Conference on Engineering Optimization, Rio de Janeiro, Brazil, 1-5 July 2012.
  18. P. O. Soares, J. Da, S. Neto, and H. Fraga De Campos Velho, “Atmospheric Temperature Profile Estimation under Clouds by Self configuring Neural Network.” Atmospheric Temperature Profile Estimation under Clouds by Self configuring Neural Network, Albi, France, June 26-28, 2013
  19. T. M. Wu and S. L. Wang, “Dynamic and fair resource allocation algorithm for OFDM systems,” IEEE Communications Letters, vol. 11, no. 12, pp. 931–933, Dec. 2007.
  20. D. Kim, T. Fujii, and K. Lee, “A resource allocation algorithm for OFDM-based cellular system serving unicast and multicast services,” Eurasip Journal on Wireless Communications and Networking, vol. 2013, no. 1, 2013.
  21. Stephen Boyd and Lieven Vandenberghe, Convex Optimization. Cambridge university press, 2009.
  22. E. Fávero Pacheco Da Luz, C. Becceneri, and H. Fraga De Campos Velho, “A new multi-particle collision algorithm for optimization in a high-performance environment 4 a new multi-particle collision algorithm for optimization in a high-performance environment,” Journal of Computational Interdisciplinary Sciences, vol. 18, no. 1, pp. 3–10, 2008, [Online]. Available: http://epacis.org
  23. Li, Sheng, Wang, and Sun, “Interference and Resource Management in Heterogeneous Wireless Networks.”
  24. TSGR, “TR 136 931 - V9.0.0 - LTE; Evolved Universal Terrestrial Radio Access (E-UTRA); Radio Frequency (RF) requirements for LTE Pico Node B (3GPP TR 36.931 version 9.0.0 Release 9),” 2011. [Online]. Available: http://portal.etsi.org/chaircor/ETSI_support.asp
  25. M. K. Ibrahim, H. M. AlSabbagh, A. Al-Omary, and H. Al-Rizzo, “Bat pack algorithm for dynamic resource allocation in OFDMA systems,” International Journal of Mobile Network Design and Innovation, vol. 9, no. 1, 2019.