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Wireless Networks

, Volume 25, Issue 6, pp 3297–3305 | Cite as

Power control algorithm based on non-cooperative game theory in successive interference cancellation

  • Renhao Sun
  • Zhenchun WeiEmail author
  • Zengwei Lyu
  • Xu Ding
  • Lei Shi
  • Songhua Hu
Article
  • 151 Downloads

Abstract

Successive interference cancellation (SIC) is an effective way of multi-packet reception to combat interference in wireless networks. The power control problem among wireless nodes in a frequency-selective interference channel is taken into consideration, which is modeled as a non-cooperative game process. Then, the existence and uniqueness of Nash equilibrium are proven. We propose a novel power control algorithm based on non-cooperative game theory that combines with the SIC conditions and constraints. A utility function refers to the network throughput and the cost function. The cost function is made up of the transmission power of each node. The wireless nodes maximize their utility by using the non-cooperative game, improving the network throughput and reducing the energy consumption. Simulation results demonstrate the effectiveness of the proposed power control strategy, which shows better performance than the other algorithms.

Keywords

Successive interference cancellation Power control Non-cooperative game theory Wireless network 

Notes

Acknowledgements

The authors would like to thank the anonymous reviewers and editors for their valuable comments. The material presented in this paper is based upon work funded by National Natural Science Foundation of China (61502142, 61501161); International Science and Technology Cooperation Program of China (2015DFI12950).

References

  1. 1.
    Sen, S., Santhapuri, N., Choudhury, R. R., & Nelakuditi, S. (2010). Successive interference cancellation: A back-of-the-envelope perspective. In ACM Workshop on Hot Topics in Networks. HOTNETS 2010, Monterey, CA, USAOctober (p. 17). DBLP.Google Scholar
  2. 2.
    Li, L. E., Alimi, R., Shen, D., & Viswanathan, H. (2010). A general algorithm for interference alignment and cancellation in wireless networks. In INFOCOM, 2010 Proceedings IEEE (Vol. 121, pp. 1–9). IEEE Xplore.Google Scholar
  3. 3.
    Ali, S., & Ahmad, A. (2017). Resource allocation, interference management, and mode selection in device-to-device communication: A survey. Transactions on Emerging Telecommunications Technologies, 28(1), 1–36.MathSciNetGoogle Scholar
  4. 4.
    Correa, A., Vicario, J. L., & Morell, A. (2015). Joint routing, channel allocation and power control for real-life wireless sensor networks. Transactions on Emerging Telecommunications Technologies, 26(5), 945–956.Google Scholar
  5. 5.
    Cho, S. E., Song, H. C., & Hodgkiss, W. S. (2011). Successive interference cancellation for underwater acoustic communications. IEEE Journal of Oceanic Engineering, 36(4), 490–501.Google Scholar
  6. 6.
    Lv, S., Zhuang, W., Xu, M., Wang, X., Liu, C., & Zhou, X. (2013). Understanding the scheduling performance in wireless networks with successive interference cancellation. IEEE Transactions on Mobile Computing, 12(8), 1625–1639.Google Scholar
  7. 7.
    Kwon, H., Lee, J., & Kang, I. (2013). Successive interference cancellation via rank-reduced maximum a posteriori detection. IEEE Transactions on Communications, 61(2), 628–637.Google Scholar
  8. 8.
    Qu, L., He, J., & Assi, C. (2014). Understanding the benefits of successive interference cancellation in multi-rate multi-hop wireless networks. IEEE Transactions on Communications, 62(7), 2465–2477.Google Scholar
  9. 9.
    Higuchi, K., & Benjebbour, A. (2015). Non-orthogonal multiple access (NOMA) with successive interference cancellation for future radio access. IEICE Transactions on Communications, E98B(3), 403–414.Google Scholar
  10. 10.
    Kontik, M., & Ergen, S. C. (2016). Distributed medium access control protocol for successive interference cancellation-based wireless ad hoc networks. IEEE Communications Letters, 21(2), 354–357.Google Scholar
  11. 11.
    Xuan, L. I., Shi, Y., Wang, X., Chao, X. U., & Sheng, M. (2016). Efficient link scheduling with joint power control and successive interference cancellation in wireless networks. Science China Information Sciences, 59(21), 1–15.Google Scholar
  12. 12.
    Cao, B., Ge, Y., Kim, C. W., Feng, G., & Tan, H. P. (2013). An experimental study for inter-user interference mitigation in wireless body sensor networks. IEEE Sensors Journal, 13(10), 3585–3595.Google Scholar
  13. 13.
    Cao, B., Qiao, L., Li, Y., Wang, C. G., & Chen, H. H. (2017). Probabilistic network coding based on buyer/seller games for retransmissions in wireless networks. IEEE Transactions on Vehicular Technology, 66(11), 1–10.Google Scholar
  14. 14.
    Cao, B., Sun, X., Li, Y., Wang, C. G., & Mei, H. (2017). Understanding the impact of employing relay node on wireless networks. IEEE Transactions on Vehicular Technology, 66(5), 4287–4299.Google Scholar
  15. 15.
    Cao, B., Chen, Q., Feng, G., Li, Y., & Wang, C. G. (2017). Revisiting relay assignment in cooperative communications. Wireless Networks, 23(2), 609–623.Google Scholar
  16. 16.
    Mohammad, M., & Buehrer, R. M. (2008). The effects of ordering criteria in linear successive interference cancellation in CDMA systems. IEEE Transactions on Wireless Communications, 7(11), 4128–4132.Google Scholar
  17. 17.
    Jalali, S., & Khalaj, B. H. (2008). Power control for multirate DS-CDMA systems with imperfect successive interference cancellation. IEEE Transactions on Vehicular Technology, 57(1), 600–603.Google Scholar
  18. 18.
    Zhang, X., & Haenggi, M. (2014). The performance of successive interference cancellation in random wireless networks. IEEE Transactions on Information Theory, 60(10), 6368–6388.MathSciNetzbMATHGoogle Scholar
  19. 19.
    Lv, S., Zhuang, W., Wang, X., & Zhou, X. (2011). Scheduling in wireless ad hoc networks with successive interference cancellation. In INFOCOM, 2011 Proceedings IEEE (Vol. 12, pp. 1287–1295). IEEE Xplore.Google Scholar
  20. 20.
    Wang, X., Shen, H., Lv, S., & Zhou, X. (2016). A genetic approach for joint link scheduling and power control in SIC-enable wireless networks. KSII Transactions on Internet & Information Systems, 10(4), 315–340.Google Scholar
  21. 21.
    Gopalakrishnan, B., & Sidiropoulos, N. D. (2013). Joint back-pressure power control and interference cancellation in wireless multi-hop networks. Wireless Communications IEEE Transactions on, 12(7), 3484–3495.Google Scholar
  22. 22.
    Yuan, D., Angelakis, V., Chen, L., & Karipidis, E. (2011). On optimal link activation with interference cancelation in wireless networking. IEEE Transactions on Vehicular Technology, 62(2), 939–945.Google Scholar
  23. 23.
    Shi, L., Shi, Y., Wei, Z., Zhou, G., & Ding, X. (2016). The power control strategy for mine locomotive wireless network based on successive interference cancellation. In Wireless Algorithms, Systems, and Applications (Vol. 9798, pp. 207–218). New York: Springer.Google Scholar
  24. 24.
    Yin, Z. L., Mao, X. P., Zhang, Q. Y., & Zhang, N. T. (2012). Fast recursive algorithm for implementation of MIMO ZF-SIC detection. Journal on Communications, 33(7), 67–74.Google Scholar
  25. 25.
    Zhou, Z. R., Li, L. M., Zhang, Y. D., & Feng, G. (2009). Joint optimization of rate allocation and decoding order adjustment in DS-CDMA systems with successive interference cancellation. Journal of Electronics & Information Technology, 31(6), 1400–1404.Google Scholar
  26. 26.
    Yin, Z., Yu, F. R., & Bu, S. (2015). Joint cloud computing and wireless networks operations: A game theoretic approach. In Global Communications Conference (pp. 4977–4982). IEEE Xplore.Google Scholar
  27. 27.
    Zhang, H., Jiang, C., Beaulieu, N. C., Chu, X., Wang, X., & Quek, T. Q. S. (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
  28. 28.
    Saraydar, C. U., Mandayam, N. B., & Goodman, D. (2001). Efficient power control via pricing in wireless data networks. IEEE Transactions on Communications, 50(2), 291–303.Google Scholar
  29. 29.
    Yu, W., Ginis, G., & Cioffi, J. M. (2002). Distributed multiuser power control for digital subscriber lines. IEEE Journal on Selected Areas in Communications, 20(5), 1105–1115.Google Scholar
  30. 30.
    Jean, C. A. S., & Jabbari, B. (2009). On game-theoretic power control under successive interference cancellation. IEEE Transactions on Wireless Communications, 8(4), 1655–1657.Google Scholar
  31. 31.
    Hu, S. H., Zhang, J. J., Lu, Y., Liu, B., & Han, J. J. (2015). Power control for successive interference cancellation algorithm based on game theory. Journal on Communications, 36(9), 215–221.Google Scholar
  32. 32.
    Jiang, C., Shi, Y., Hou, Y. T., & Lou, W. (2012). Squeezing the most out of interference: An optimization framework for joint interference exploitation and avoidance. In INFOCOM, 2012 Proceedings IEEE (Vol. 131, pp. 424–432). IEEE Xplore.Google Scholar
  33. 33.
    Goodman, D., & Mandayam, N. (2000). Power control for wireless data. IEEE Personal Communications, 7(2), 48–54.zbMATHGoogle Scholar
  34. 34.
    Yates, R. D. (1995). A framework for uplink power control in cellular radio systems. IEEE Journal on Selected Areas in Communications, 13(7), 1341–1347.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Computer and InformationHefei University of TechnologyHefeiPeople’s Republic of China

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