Skip to main content
SpringerLink
Log in

An Evolutionary Game-Theoretic Approach for Base Station Allocation in Wireless Femtocell Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The deployment of femtocell is as a potential solution to improving the indoor coverage and capacity of a cellular network. However, providing quality of service (QoS) is one of the most significant challenges in wireless femtocell networks. Cellular users with different QoS requirements always look for a serving base station (BS) to achieve their desired QoS. Therefore, intelligent BS allocation plays a crucial role in guaranteeing the QoS. In this paper, we propose a game-theoretic BS allocation approach with a QoS guarantee for downlink femtocell networks. We model the BS allocation problem as an evolutionary game in which users with bounded rationality learn from the environment and make BS selection decisions with minimum exchange of information. In the propounded model, not only do we consider the users’ QoS, but we also take account of macro users’ activity as an interferer to reduce the cross-tier interference. Unlike the previous studies, we calculate the demand rejection probability for each user associated with a BS to evaluate statistical QoS guarantees. A distributed learning-based algorithm is developed to show the existence and fairness of the solution to our proposed model and to demonstrate the convergence to the evolutionary equilibrium as the solution of the game. Simulation results verify the effectiveness, performance improvement, and good convergence of the proposed approach.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

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

Similar content being viewed by others

References

  1. Chandrasekhar, V., Andrews, J. G., & Gatherer, A. (2008). Femtocell networks: A survey. IEEE Communications Magazine, 46(9), 59–67.

    Google Scholar 

  2. Guan, X., Han, Q., Ma, K., & Wang, X. (2013). Robust uplink power control for co-channel two-tier femtocell networks. AEU-International Journal of Electronics and Communications, 67(6), 504–512.

    Google Scholar 

  3. Yaacoub, E., & Dawy, Z. (2011). Interference mitigation and avoidance in uplink OFDMA with collaborative distributed intracell scheduling. AEU-International Journal of Electronics and Communications, 65(11), 937–941.

    Google Scholar 

  4. Andrews, J. G., Claussen, H., Dohler, M., Rangan, S., & Reed, M. C. (2012). Femtocells: Past, present, and future. IEEE Journal on Selected Areas in Communications, 30(3), 497–508.

    Google Scholar 

  5. Knisely, D. N., Yoshizawa, T., & Favichia, F. (2009). Standardization of femtocells in 3GPP. IEEE Communications Magazine, 47(9), 68–75.

    Google Scholar 

  6. Madan, R., Borran, J., Sampath, A., Bhushan, N., Khandekar, A., & Ji, T. (2010). Cell association and interference coordination in heterogeneous LTE-A cellular network. IEEE Journal on Selected Areas in Communications, 28(9), 1479–1489.

    Google Scholar 

  7. Prajapati, D., & Richhariya, V. (2014). A survey on cell selection schemes for femtocell networks. In Proceedings of IEEE personal, indoor and mobile radio communications (PIMRC) (Vol. 3, No. 7, pp. 465–468).

  8. Ye, Q., Rong, B., Chen, Y., Al-Shalash, M., Caramanis, C., & Andrews, J. G. (2013). User association for load balancing in heterogeneous cellular networks. IEEE Transactions on Wireless Communications, 12(6), 2706–2716.

    Google Scholar 

  9. Du, H., Zhou, Y., Tian, L., Wang, X., Pan, Z., Shi, J., et al. (2015). A load fairness aware cell association for centralized heterogeneous networks. IEEE International Conference on Communications (ICC), 2015, 2178–2183.

    Google Scholar 

  10. Zhang, Y. J., & Letaief, K. B. (2004). Multiuser adaptive subcarrier-and-bit allocation with adaptive cell selection for OFDM systems. IEEE Transactions on Wireless Communications, 3(5), 1566–1575.

    Google Scholar 

  11. Feng, M., She, X., Chen, L., & Kishiyama, Y. (2010). Enhanced dynamic cell selection with muting scheme for DL CoMP in LTE-A. In Vehicular technology conference (VTC), IEEE 71st, pp. 1–5.

  12. Liang, Y. S., Chung, W. H., Ni, G. K., Chen, Y., Zhang, H., & Kuo, S. Y. (2012). Resource allocation with interference avoidance in OFDMA femtocell networks. IEEE Transactions on Vehicular Technology, 61(5), 2243–2255.

    Google Scholar 

  13. Zhou, H., Hu, D., Mao, S., Agrawal, P., & Reddy. SA. (2013). Cell association and handover management in femtocell networks. In Wireless communications and networking conference (WCNC) (pp. 661–666). IEEE.

  14. Xu, Y., Hu, R., Wei, L., & Wu, G. (2014). QoE-aware mobile association and resource allocation over wireless heterogeneous networks. In Proceedings of 2014 IEEE global communications conference (GLOBECOM), December 2014 (pp. 4695–4701).

  15. Fooladivanda, D., Al Daoud, A., & Rosenberg, C. (2011). Joint channel allocation and user association for heterogeneous wireless cellular networks. In Proceedings of 2011 IEEE 22nd international symposium on personal, indoor and mobile radio communications (PIMRC), September 2011 (pp. 384–390).

  16. Corroy, S., Falconetti, L., & Mathar, R. (2012). Dynamic cell association for downlink sum rate maximization in multi-cell heterogeneous networks. In Proceeding of IEEE international conference on communications (ICC), June 2012 (pp. 2457–2461).

  17. Nguyen, K. D., Nguyen, H. N., Morino, H., & Sasase, I. (2014). Uplink channel allocation scheme and qos management mechanism for cognitive cellular-femtocell networks. International Journal of Communication Networks and Information Security, 6(1), 62.

    Google Scholar 

  18. Xu, Y., & Mao, S. (2017). User association in massive MIMO HetNets. IEEE Systems Journal, 11(1), 7–19.

    Google Scholar 

  19. Jo, H. S., Sang, Y. J., Xia, P., & Andrews, J. G. (2012). Heterogeneous cellular networks with flexible cell association: A comprehensive downlink SINR analysis. IEEE Transactions on Wireless Communications, 11(10), 3484–3495.

    Google Scholar 

  20. Zhang, H., Huang, S., Jiang, C., Long, K., Leung, V. C., & Poor, H. V. (2017). Energy efficient user association and power allocation in millimeter-wave-based ultra-dense networks with energy harvesting base stations. IEEE Journal on Selected Areas in Communications, 35(9), 1936–1947.

    Google Scholar 

  21. ElSawy, H., & Hossain, E. (2014). Two-tier HetNets with cognitive femtocells: Downlink performance modeling and analysis in a multichannel environment. IEEE Transactions on Mobile Computing, 13(3), 649–663.

    Google Scholar 

  22. Myerson, R. B. (2013). Game theory. Harvard: Harvard University Press.

    MATH  Google Scholar 

  23. Zhang, X., Zhang, Y., Shi, Y., Zhao, L., & Zou, C. (2012). Power control algorithm in cognitive radio system based on modified shuffled frog leaping algorithm. AEU-International Journal of Electronics and Communications, 66(6), 448–454.

    Google Scholar 

  24. Liu, X., Ding, G., Yang, Y., Wu, Q., & Wang, J. (2013). A stochastic game framework for joint frequency and power allocation in dynamic decentralized cognitive radio networks. AEU-International Journal of Electronics and Communications, 67(10), 817–826.

    Google Scholar 

  25. Zhu, K., Hossain, E., & Niyato, D. (2014). Pricing, spectrum sharing, and service selection in two-tier small cell networks: A hierarchical dynamic game approach. IEEE Transactions on Mobile Computing, 13(8), 1843–1856.

    Google Scholar 

  26. Bayat, S., Louie, R. H., Han, Z., Vucetic, B., & Li, Y. (2014). Distributed user association and femtocell allocation in heterogeneous wireless networks. IEEE Transactions on Communications, 62(8), 3027–3043.

    Google Scholar 

  27. Ha, V. N., & Le, L. B. (2014). Distributed base station association and power control for heterogeneous cellular networks. IEEE Transactions on Vehicular Technology, 63(1), 282–296.

    Google Scholar 

  28. Zhang, H., Jiang, C., Beaulieu, N. C., Chu, X., Wang, X., & Quek, T. Q. (2015). Resource allocation for cognitive small cell networks: A cooperative bargaining game theoretic approach. IEEE Transactions on Wireless Communications, 14(6), 3481–3493.

    Google Scholar 

  29. Lien, S. Y., Lin, Y. Y., & Chen, K. C. (2011). Cognitive and game-theoretical radio resource management for autonomous femtocells with QoS guarantees. IEEE Transactions on Wireless Communications, 10(7), 2196–2206.

    Google Scholar 

  30. Weibull, J. W. (1997). Evolutionary game theory. Cambridge: MIT Press.

    MATH  Google Scholar 

  31. Feng, Z., Song, L., Han, Z., & Zhao, X. (2013). Cell selection in two-tier femtocell networks with open/closed access using evolutionary game. In Wireless Communications and networking conference (WCNC) (pp. 860–865). IEEE.

  32. Bennis, M., Guruacharya, S., & Niyato, D. (2011). Distributed learning strategies for interference mitigation in femtocell networks. In Global telecommunications conference (GLOBECOM 2011) (pp. 1–5). IEEE.

  33. Semasinghe, P., Hossain, E., & Zhu, K. (2015). An evolutionary game for distributed resource allocation in self-organizing small cells. IEEE Transactions on Mobile Computing, 14(2), 274–287.

    Google Scholar 

  34. Niyato, D., & Hossain, E. (2009). Dynamics of network selection in heterogeneous wireless networks: An evolutionary game approach. IEEE Transactions on Vehicular Technology, 58(4), 2008–2017.

    Google Scholar 

  35. Wu, D., & Negi, R. (2003). Effective capacity: A wireless link model for support of quality of service. IEEE Transactions on Wireless Communications, 2(4), 630–643.

    Google Scholar 

  36. 3GPP Technical Specification TS 23.207. (2009). End-to-end QoS concept and architecture. http://www.3gpp.org.

  37. Chang, C. S., & Thomas, J. A. (1995). Effective bandwidth in high-speed digital networks. IEEE Journal on Selected Areas in Communications, 13(6), 1091–1100.

    Google Scholar 

  38. Chang, C. S. (1994). Stability, queue length, and delay of deterministic and stochastic queueing networks. IEEE Transactions on Automatic Control, 39(5), 913–931.

    MathSciNet  MATH  Google Scholar 

  39. Andrews, J. G., Baccelli, F., & Ganti, R. K. (2011). A tractable approach to coverage and rate in cellular networks. IEEE Transactions on Communications, 59(11), 3122–3134.

    Google Scholar 

  40. Sandholm, W. H. (2010). Population games and evolutionary dynamics. Cambridge, MA: MIT Press.

    MATH  Google Scholar 

  41. Auer, P., Cesa-Bianchi, N., Freund, Y., & Schapire, R. E. (2002). The non-stochastic multi-armed bandit problem. SIAM Journal on Computing, 32(1), 48–77.

    MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Azadeh Pourkabirian & Amir Masoud Rahmani

  2. Department of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran, Iran

    Mehdi Dehghan Takht Fooladi

  3. Department of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

    Esmaeil Zeinali Khosraghi

Authors
  1. Azadeh Pourkabirian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mehdi Dehghan Takht Fooladi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Esmaeil Zeinali Khosraghi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Amir Masoud Rahmani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Esmaeil Zeinali Khosraghi.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pourkabirian, A., Dehghan Takht Fooladi, M., Zeinali Khosraghi, E. et al. An Evolutionary Game-Theoretic Approach for Base Station Allocation in Wireless Femtocell Networks. Wireless Pers Commun 107, 217–242 (2019). https://doi.org/10.1007/s11277-019-06251-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-019-06251-y

Keywords

Search

Navigation