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Multi-objective Power Control Algorithm for Femtocell Networks

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Abstract

Future wireless networks are designed to cope with drastically increasing user demands. However, network resources reach the limits of their capacity to user requirements. Recently, femtocell has appeared as an effective solution to achieve larger coverage for indoor users while improving the cellular network capacity. In femtocell networks, the most important issue is to design an efficient and fair power control protocol, which can significantly influences the network performance. In this paper, a new multi-objective power control algorithm is developed based on the no-regret learning technique and intervention game model. The proposed control paradigm can provide the ability to practically respond to current system conditions and suitable for real network operations. Under a dynamically changing network environment, the proposed approach appropriately controls the power level to balance network performance between efficiency and fairness.

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References

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

    Article  Google Scholar 

  2. Chowdhury, M. Z., Bui, M. T., & Jang, Y. M. (2011). Neighbor cell list optimization for femtocell-to-femtocell Handover in dense femtocellular networks. In International conference on ubiquitous and future, networks (ICUFN’11) (pp. 241–245).

  3. Li, Y., & Feng, Z. (2011). Enterprise femtocell network optimization based on neural network modeling. IEEE CCNC’11 (pp. 1130–1131).

  4. Hong, E., Yun S., & Cho D. (2009). Decentralized power control scheme in femtocell networks: A game theoretic approach. IEEE PIMRC (pp. 415–419).

  5. Lu, Z., Sun, Y., Wen, X., Su, T. & Ling D. (2012). An energy-efficient power control algorithm in femtocell networks. IEEE ICCSE (pp. 395–400).

  6. Dianati, M., Shen, X., & Naik, S. (2005, March). A new fairness index for radio resource allocation in wireless networks. In Proc. of IEEE WCNC, vol. 2 (pp. 712–715).

  7. Mo, J., & Walrand, J. (2000). Fair end-to-end window-based congestion control. IEEE/ACM Transactions on Networking, 8(5), 556–567.

    Article  Google Scholar 

  8. Li, J., Shi, Z., Liu, W.-Y., Yue, K., & Chen, R.-J. (2010). No-regret learning for cost constrained resource selection game. ICNC 2010, (pp. 2921–2925).

  9. Kim, S. (2011). An adaptive online power control scheme based on the evolutionary game theory. IET Communications, 5(18), 2648–2655.

    Google Scholar 

  10. Park, J., & van der Schaar, M. (2012). The theory of intervention games for resource sharing in wireless communications. IEEE Journal on Selected Areas in Communications, 30(1), 165–175.

    Google Scholar 

  11. Park , J., & van der Schaar, M. (2011). A note on the intervention, framework.

  12. Hart, S., & Mas-Colell, A. (2000). A simple adaptive procedure leading to correlated equilibrium. Econometrica, 68(5), 1127–1150.

    Google Scholar 

  13. Latifa, B., Gao, Z., & Liu, S. (2012). No-regret learning for simultaneous power control and channel allocation in cognitive radio networks. In IEEE ComComAp’2012 (pp. 267–271).

  14. Xiao, Y., Park, J., & van der Schaar, M. (2012). Intervention in power control games with selfish users. IEEE Journal on Selected Areas in Communications, 6(2), 165–179.

    Google Scholar 

  15. Altman, E. Avrachenkov, K. & Garnaev, A. (2008). Generalized \(\alpha \)-fair resource allocation in wireless networks. In IEEE CDC (pp. 2414–2419).

  16. Altman, E., Avrachenkov, K., & Garnaev, A. (2010). Fair resource allocation in wireless networks in the presence of a jammer. Performance Evaluation, 67, 338–349.

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Computer Science, Sogang University, 35 Baekbeom-ro (Sinsu-dong), Mapo-gu, Seoul, 121-742, South Korea

    Sungwook Kim

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  1. Sungwook Kim
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Correspondence to Sungwook Kim.

Additional information

This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology(NRF-2011-0015912) and by the Sogang University Research Grant of 201110011.

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Kim, S. Multi-objective Power Control Algorithm for Femtocell Networks. Wireless Pers Commun 75, 2281–2288 (2014). https://doi.org/10.1007/s11277-013-1467-3

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  • DOI: https://doi.org/10.1007/s11277-013-1467-3

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