Skip to main content

Advertisement

Log in

Maximum rate resource allocation algorithms with multiuser diversity and QoS support for downlink OFDMA based WiMAX system

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

Orthogonal frequency division multiple access (OFDMA) has been adopted as the core physical layer access for a few broadband wireless access networks such as worldwide interoperability for microwave access (WiMAX). In WiMAX the primary concern is quality of service (QoS) support which aims to satisfy the diverse service requirements and to guarantee the required data rates from the available resources. Therefore, designing resource allocation algorithm becomes vital to maximize spectral efficiency. In this paper, two resource allocation algorithms are proposed, namely, weighted-rate adaptive slot allocation (WASA), and feedback delay-based slot allocation (FDSA) for OFDMA downlink system. The aim is to improve system performance by exploiting the available resources in a two-dimensional domain, and assigning the capacity for each user based on their achievable data rates and channel responses. During all these processes, fairness for all service types is ensured. Both approaches allocate appropriate resources and provide higher data rates for different service types by employing a weighted-rate factor and feedback information delay which are made to be greater than the minimum QoS requirements. Simulation results indicate that both WASA and FDSA achieve significant performance improvements in terms of spectral efficiency, outage probability, and fairness against the conventional OFDMA-TDMA and MAX-SNR algorithms. Comparison with recent works developed as adaptive slot allocation and reservation-based slot allocation has also been performed. The performance gains of both our proposed algorithms can be attributed to satisfying of the diverse multiuser and QoS requirements.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. IEEE Std 802.16e. (2006). IEEE Standard for local and metropolitan area networks. Part 16: air interface for fixed and mobile broadband wireless access systems.

  2. Prasad, R. (2004). OFDM for wireless communications systems.

  3. IEEE 802.16m. (2010). IEEE Draft Amendment Standard for Local and Metropolitan Area Networks. Part 16: Air Interface for Broadband Wireless Access Systems–Advanced Air Interface, D10, p. 1–1132.

  4. Keller, T., & Hanzo, L. (2000). Adaptive modulation techniques for duplex OFDM transmission. IEEE Transactions on Vehicular Technology, 49(5), 1893–1906.

    Article  Google Scholar 

  5. Zhang, Y., & Leung, C. (2009). Cross-layer resource allocation for real-time services in OFDM-based cognitive radio systems. Telecommunication Systems, 42(1–2), 97–108.

    Article  Google Scholar 

  6. Song, G., & Li, Y. (2005). Cross-layer optimization for OFDM wireless networks-part II: Algorithm development. IEEE Transactions on Wireless Communications, 4(2), 625–634.

    Article  Google Scholar 

  7. Rong, B., Qian, Y., & Lu, K. (2007). Integrated downlink resource management for multiservice WiMAX networks. IEEE Transactions on Mobile Computing, 6(6), 621–632.

    Article  Google Scholar 

  8. Femenias, G., Daobeitia, B., & Riera-Palou, F. (2012). Unified approach to cross-layer scheduling and resource allocation in OFDMA wireless networks. EURASIP Journal on Wireless Communications and Networking, 145, 1–19.

    Google Scholar 

  9. Tarhini, C., & Chahed, T. (2012). QoS-oriented resource allocation for streaming flows in IEEE802. 16e Mobile WiMAX. Telecommunication Systems, 51(1), 65–71.

    Article  Google Scholar 

  10. Wang, H., & Dittmann, L. (2010). Downlink resource management for QoS scheduling in IEEE 802.16 WiMAX networks. Computer Communications, 33(8), 940–953.

    Article  Google Scholar 

  11. Nguyen, T.-D., & Han, Y. (2006). A proportional fairness algorithm with QoS provision in downlink OFDMA systems. IEEE Communications Letters, 10(11), 760–762.

    Article  Google Scholar 

  12. Ergen, M., Coleri, S., & Varaiya, P. (2003). QoS aware adaptive resource allocation techniques for fair scheduling in OFDMA based broadband wireless access systems. IEEE Transactions on Broadcasting, 49(4), 362–370.

    Article  Google Scholar 

  13. Girici, T., et al. (2010). Proportional fair scheduling algorithm in OFDMA-based wireless systems with QoS constraints. Journal of Communications and Networks, 12(1), 30–42.

  14. Gyasi-Agyei, A., & Kim, S.-L. (2006). Cross-layer multiservice opportunistic scheduling for wireless networks. IEEE Communications Magazine, 44(6), 50–57.

    Article  Google Scholar 

  15. Choi, K. W., Jeon, W. S., & Jeong, D. G. (2009). Resource allocation in OFDMA wireless communications systems supporting multimedia services. IEEE/ACM Transactions on Networking, 17(3), 926–935.

    Article  Google Scholar 

  16. Ali-Yahiya, T., Beylot, A.-L., & Pujolle, G. (2010). Downlink resource allocation strategies for OFDMA based mobile WiMAX. Telecommunication Systems, 44(1–2), 29–37.

    Article  Google Scholar 

  17. Liu, Y., et al. (2010). A novel QoS-oriented packet scheduling algorithm for mixed services in the downlink of OFMDA system. In IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS).

  18. Tarhini, C., & Chahed T. (2007). AMC-aware QoS proposal for OFDMA-based IEEE802. 16 WiMAX systems. In IEEE Global Telecommunications Conference (GLOBECOM’07).

  19. Qiu, X., & Chawla, K. (1999). On the performance of adaptive modulation in cellular systems. IEEE Transactions on Communications, 47(6), 884–895.

    Article  Google Scholar 

  20. Zhang, X., & Wang, W. (2006). Multiuser frequency-time domain radio resource allocation in downlink OFDM systems: Capacity analysis and scheduling methods. Computers & Electrical Engineering, 32(1), 118–134.

    Article  Google Scholar 

  21. Aweya, J., Ouellette, M., & Montuno, D. Y. (2002). Stability and fairness of a rate allocation scheme. Telecommunication Systems, 20(3–4), 195–239.

    Article  Google Scholar 

  22. Alsahag, A. M., et al. (2013). Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin. Journal of Network and Computer Applications.

  23. Reklaitis, G., Ravindran, A., & Ragsdell, K. (1983). Engineering optimization methods and applications. New York: Wiley.

    Google Scholar 

  24. Jain, R., Chiu, D.-M., & Hawe, W. R. (1984). A quantitative measure of fairness and discrimination for resource allocation in shared computer system. Hudson, MA: Eastern Research Laboratory, Digital Equipment Corporation.

    Google Scholar 

Download references

Acknowledgments

The authors would like to acknowledge the Ministry of Higher Education of Malaysia for the partial financial support.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ali Mohammed Alsahag.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Alsahag, A.M., Ali, B.M., Noordin, N.K. et al. Maximum rate resource allocation algorithms with multiuser diversity and QoS support for downlink OFDMA based WiMAX system. Telecommun Syst 63, 1–14 (2016). https://doi.org/10.1007/s11235-015-9967-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-015-9967-y

Keywords

Navigation