Radio resource management based on reused frequency allocation for dynamic channel borrowing scheme in wireless networks

Abstract

In the modern era, cellular communication consumers are exponentially increasing as they find the system more user-friendly. Due to enormous users and their numerous demands, it has become a mandate to make the best use of the limited radio resources that assures the highest standard of Quality of Service (QoS). To reach the guaranteed level of QoS for the maximum number of users, maximum utilization of bandwidth is not only the key issue to be considered, rather some other factors like interference, call blocking probability etc. are also needed to keep under deliberation. The lower performances of these factors may retrograde the overall cellular networks performances. Keeping these difficulties under consideration, we propose an effective dynamic channel borrowing model that safeguards better QoS, other factors as well. The proposed scheme reduces the excessive overall call blocking probability and does interference mitigation without sacrificing bandwidth utilization. The proposed scheme is modeled in such a way that the cells are bifurcated after the channel borrowing process if the borrowed channels have the same type of frequency band (i.e. reused frequency). We also propose that the unoccupied interfering channels of adjacent cells can also be inactivated, instead of cell bifurcation for interference mitigation. The simulation endings show satisfactory performances in terms of overall call blocking probability and bandwidth utilization that are compared to the conventional scheme without channel borrowing. Furthermore, signal to interference plus noise ratio level, capacity, and outage probability are compared to the conventional scheme without interference mitigation after channel borrowing that may attract the considerable concentration to the operators.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

References

  1. 1.

    Chowdhury, M. Z., Jang, Y. M., & Haas, Z. J. (2013). Call admission control based on adaptive bandwidth allocation for wireless networks. IEEE/KICS Journal of Communications and Networks, 15(1), 15–24.

    Article  Google Scholar 

  2. 2.

    Rahman, M., & Yanikomeroglu, H. (2010). Enhancing cell-edge performance: A downlink dynamic interference avoidance scheme with inter-cell coordination. IEEE Transactions on Wireless Communications, 9(4), 1414–1425.

    Article  Google Scholar 

  3. 3.

    Attar, A., Krishnamurthy, V., & Gharehshiran, O. N. (2011). Interference management using cognitive base-stations for UMTS LTE. IEEE Communications Magazine, 49(8), 152–159.

    Article  Google Scholar 

  4. 4.

    Chowdhury, M. Z., Jang, Y. M., & Haas, Z. J. (2013). Radio resource allocation for scalable video services over wireless cellular networks. Wireless Personal Communications, 74(3), 1061–1079.

    Article  Google Scholar 

  5. 5.

    Wang, X., Fan, P., & Pan, Y. (2008). A more realistic thinning scheme for call admission control in multimedia wireless networks. IEEE Transactions on Computers, 57(8), 1143–1148.

    MathSciNet  Article  Google Scholar 

  6. 6.

    Elayoubi, S. E., Haddada, O. B., & Fouresti, B. (2008). Performance evaluation of frequency planning schemes in ofdma-based networks. IEEE Transactions on Wireless Communications, 7(5), 1623–1633.

    Article  Google Scholar 

  7. 7.

    Ali, S. H., & Leung, V. C. M. (2009). Dynamic frequency allocation in fractional frequency reused ofdma networks. IEEE Transactions on Wireless Communications, 8(8), 4286–4295.

    Article  Google Scholar 

  8. 8.

    Xu, Z., Mirchandani, P. B., & Xu, S. H. (2000). Virtually fixed channel assignment in cellular mobile networks with recall and handoffs. Telecommunication Systems, 13(2–4), 413–439.

    Article  MATH  Google Scholar 

  9. 9.

    Vidyarthi, G., Ngom, A., & Stojmenovic, I. (2005). A hybrid channel assignment approach using an efficient evolutionary strategy in wireless mobile networks. IEEE Transactions on Vehicular Technology, 54(5), 1887–1895.

    Article  Google Scholar 

  10. 10.

    Jiang, H., & Rappaport, S. S. (1999). Channel borrowing without locking for asynchronous hybrid FDMA/TDMA cellular communications. Wireless Personal Communication, 9(3), 233–254.

    Article  Google Scholar 

  11. 11.

    Son, K., & Chong, S. (2009). Dynamic association for load balancing and interference avoidance in multi-cell networks. IEEE Transactions on Wireless Communications, 8(7), 3566–3576.

    Article  Google Scholar 

  12. 12.

    Zhang, X., He, C., Jiang, L., & Xu, J. (2008). Inter-cell interference coordination based on softer frequency reuse in OFDMA cellular systems. In Proceeding of IEEE international conference neural networks & signal processing, June 8 (pp. 270–275).

  13. 13.

    Wang, X., & Zhu, S. (2009) Mitigation of intercarrier interference based on general precoder design in OFDM systems. In Proceeding of international conference on advanced information networking and applications, May 27, (pp. 705–710).

  14. 14.

    Iyer, A., Rosenberg, C., & Karnik, A. (2009). What is the right model for wireless channel interference? IEEE Transactions on Wireless Communications, 8(5), 2662–2671.

    Article  Google Scholar 

  15. 15.

    Oh, E., Han, S., Woo, C., & Hong, D. (2008). Call admission control strategy for system throughput maximization considering both call and packet-level QoSs. IEEE Transactions on Communications, 56(10), 1591–1595.

    Article  Google Scholar 

  16. 16.

    Kim, H.-S., Kim, D.-R., Yang, S.-H., Son, Y.-H., & Han, S.-K. (2012). Mitigation of inter-cell interference utilizing carrier allocation in visible light communication system. IEEE Communications Letters, 16(4), 526–529.

    Article  Google Scholar 

  17. 17.

    Chowdhury, M. Z., Lee, S. Q., Ru, B. H., Park, N., & Jang, Y. M. (2011). Service quality improvement of mobile users in vehicular environment by mobile femtocell network deployment. In Proceeding of IEEE international conference on ICT convergence, September 2011 (pp. 194–198).

  18. 18.

    Chowdhury, M. Z., Jang, Y. M., & Haas, Z. J. (2011). Cost-effective frequency planning for capacity enhancement of femtocellular networks. Wireless Personal Communications, 60(1), 83–104.

    Article  Google Scholar 

  19. 19.

    Ni, S., Liang, Y., & Häggman, S.-G. (2000). Outage probability in GSM–GPRS cellular systems with and without frequency hopping. Wireless Personal Communication, 14(3), 215–234.

    Article  Google Scholar 

  20. 20.

    Gastpar, M. (2007). On capacity under receive and spatial spectrum-sharing constraints. IEEE Transaction Information Theory, 53(2), 471–487.

    MathSciNet  Article  Google Scholar 

Download references

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2013057922).

Author information

Affiliations

Authors

Corresponding author

Correspondence to Mostafa Zaman Chowdhury.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chowdhury, M.Z., Hossain, M.A., Ahmed, S. et al. Radio resource management based on reused frequency allocation for dynamic channel borrowing scheme in wireless networks. Wireless Netw 21, 2593–2607 (2015). https://doi.org/10.1007/s11276-015-0937-9

Download citation

Keywords

  • Dynamic channel borrowing
  • Quality of Service (QoS)
  • Bandwidth utilization
  • Interference mitigation
  • Outage probability
  • Channel capacity