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Wireless Networks

, Volume 25, Issue 6, pp 3005–3018 | Cite as

Dynamic energy-efficient resource allocation in wireless powered communication network

  • Jiangqi Hu
  • Qinghai YangEmail author
Article
  • 137 Downloads

Abstract

In this paper, we investigate the dynamic energy-efficient resource allocation and analyze delay in newly emerging wireless powered communication network (WPCN). Considering the time-varying channel and stochastic data arrivals, we formulate the resource allocation (i.e., time allocation and power control) problem as a dynamic stochastic optimization model, which maximizes the system energy efficiency (EE) subject to both the data queue stability and the harvested energy availability, and simultaneously satisfies a certain quality of service (QoS) in terms of delay. With the aid of fractional programming, Lyapunov optimization theory and Lagrange method, we solve the problem and propose an dynamic energy-efficient resource allocation algorithm (DEERAA), which does not require any prior distribution knowledge of the channel state information (CSI) or stochastic data arrivals. We find that the performance of EE and delay can be adjusted by a system control parameter V. The effectiveness of the proposed algorithm is demonstrated by the mathematical analysis and simulation results.

Keywords

WPCN Energy efficiency Delay Dynamic resource allocation 

References

  1. 1.
    Guo, J., Zhao, N., Yu, F. R., Liu, X., & Leung, V. C. M. (2017). Exploiting adversarial jamming signals for energy harvesting in interference networks. IEEE Transactions on Wireless Communications, 16(2), 1267–1280.CrossRefGoogle Scholar
  2. 2.
    Guo, J., Zhao, N., Yu, F. R., Liu X., & Leung, V. C. M. (2016). Wireless energy harvesting in interference alignment networks with adversarial jammers. (2016) In 8th International conference on wireless communications & signal processing (WCSP), Yangzhou, pp. 1–5.Google Scholar
  3. 3.
    Zhao, N., Yu, F. R., & Leung, V. C. M. (2015). Opportunistic communications in interference alignment networks with wireless power transfer. IEEE Wireless Communications, 22(1), 88–95.CrossRefGoogle Scholar
  4. 4.
    Chang, Z., et al. (2016). Energy efficient resource allocation for wireless power transfer enabled collaborative mobile clouds. IEEE Journal on Selected Areas in Communications, 34(12), 3438–3450.CrossRefGoogle Scholar
  5. 5.
    Chang, Z., Wang, Z., Guo, X., Han, Z., & Ristaniemi, T. Energy-Efficient Resource Allocation for Wireless Powered Massive MIMO System With Imperfect CSI. in IEEE Transactions on Green Communications and Networking, 1(2), 121–130.Google Scholar
  6. 6.
    Chang, Z., Gong, J., Ristaniemi, T., & Niu, Z. (2016). Energy-efficient resource allocation and user scheduling for collaborative mobile clouds with hybrid receivers. IEEE Transactions on Vehicular Technology, 65(12), 9834–9846.CrossRefGoogle Scholar
  7. 7.
    Tang, J., So, D. K. C., Shojaeifard, A., Wong, K. K., & Wen, J. (2017). Joint antenna selection and spatial switching for energy efficient MIMO SWIPT system. IEEE Transactions on Wireless Communications, 16(7), 4754–4769.CrossRefGoogle Scholar
  8. 8.
    Huang, K., & Lau, V. (2014). Enabling wireless power transfer in cellular networks: Architecture, modeling and deployment. IEEE Transactions on Wireless Communications, 13(2), 902–912.CrossRefGoogle Scholar
  9. 9.
    Ng, D. W. K., Lo, E. S., & Schober, R. (2013). Energy-efficient resource allocation in OFDMA systems with hybrid energy harvesting base station. IEEE Transactions on Wireless Communications, 12(7), 3412–3427.CrossRefGoogle Scholar
  10. 10.
    Nintanavongsa, P., et al. (2012). Design optimization and implementation for RF energy harvesting circuits. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2(1), 24–33.CrossRefGoogle Scholar
  11. 11.
    Kim, J., Lee, H., Song, C., Oh, T., & Lee, I. (2016). Sum throughput maximization for multi-user MIMO cognitive wireless powered communication networks. IEEE Transactions on Communications, 16(10), 913–923.Google Scholar
  12. 12.
    Lee, H., Lee, K. J., Kim, H., Clerckx, B., & Lee, I. (2016). Resource allocation techniques for wireless powered communication networks with energy storage constraint. IEEE Transactions on Wireless Communications, 15(4):2619-2628.Google Scholar
  13. 13.
    Li, H., Song, L., & Debbah, M. (2014). Energy efficiency of large-scale multiple antenna systems with transmit antenna selection. IEEE Transactions on Communications, 62(2), 638–647.CrossRefGoogle Scholar
  14. 14.
    Xiong, C., Li, G., Zhang, S., Chen, Y., & Xu, S. (2012). Energy-efficient resource allocation in OFDMA networks. IEEE Transactions on Communications, 60(12), 3767–3778.CrossRefGoogle Scholar
  15. 15.
    Lin, X., Huang, L., Guo, C., Zhang, P., Huang, M., & Zhang, J. (2017). Energy-efficient resource allocation in TDMS-based wireless powered communication networks. IEEE Communications Letters, 21(4), 861–864.CrossRefGoogle Scholar
  16. 16.
    Kim, W., & Yoon, W. (2016). Energy efficiency maximisation for WPCN with distributed massive MIMO system. Electronics Letters, 52(19), 1642–1644 9 15.Google Scholar
  17. 17.
    Salem, A., & Hamdi, K. A., (2016). Wireless Power Transfer in Two-Way AF Relaying Networks. IEEE global communications conference (GLOBECOM). Washington, DC, 2016, 1–6.Google Scholar
  18. 18.
    Wu, Q., Chen, W., Kwan Ng, D. W., Li, J., & Schober, R. (2016). User-centric energy efficiency maximization for wireless powered communications. IEEE Transactions on Wireless Communications, 15(10), 6898–6912.CrossRefGoogle Scholar
  19. 19.
    Wu, Q., Tao, M., Kwan Ng, D. W., Chen, W., & Schober, R. (2016). Energy-efficient resource allocation for wireless powered communication networks. IEEE Transactions on Wireless Communications, 15(3), 2312–2327.CrossRefGoogle Scholar
  20. 20.
    Yang, J., Yang, Q., Kwak, K. S., & Rao, R. R. (2017). Power-delay tradeoff in wireless powered communication networks. IEEE Transactions on Vehicular Technology, 66(4), 3280–3292.CrossRefGoogle Scholar
  21. 21.
    Huang, W., Chen, H., Li, Y., & Vucetic, B. (2016). On the performance of multi-antenna wireless-powered communications with energy beamforming. IEEE Transactions on Vehicular Technology, 65(3), 1801–1808.CrossRefGoogle Scholar
  22. 22.
    Li, Y., Sheng, M., & Shi, Y. (2014). Energy efficiency and delay tradeoff for time-varying and interference-free wireless networks.IEEE Transactions on Wireless Communications,13(11), pp. 5921–5931.Google Scholar
  23. 23.
    Peng, M., Yu, Y., Xiang, H., & Poor, H. V. (2016). Energy-efficient resource allocation optimization for multimedia heterogeneous cloud radio access networks. IEEE Transactions on Multimedia, 18(5), 879–892.CrossRefGoogle Scholar
  24. 24.
    Kang, X., HO, C. K., & Sun, S. (2015). Full-duplex wireless-powered communication network with energy causality. IEEE Transactions on Wireless Communications, 14(10), 5539–5551.CrossRefGoogle Scholar
  25. 25.
    Zhou, X., Ho, C. K., & Zhang, R. (2016). Wireless power meets energy harvesting: A joint energy allocation approach in OFDM-based system. IEEE Transactions on Wireless Communications, 15(5), 3481–3491.CrossRefGoogle Scholar
  26. 26.
    Bersekas, D., & Gallager, R. (1987). Data Networks. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  27. 27.
    Wu, Q., Tao, M., Ng, D. W. K., Chen, W., & Schober, R. (2015). Energy-efficient transmission for wireless powered multiuser communication networks. 2015 IEEE International Conference on Communications (ICC), IEEE. pp. 154–159.Google Scholar
  28. 28.
    Bersekas, D., & Tsitaiklia, J. (1996). Neuro-dynamic programming. Belmont: Athena Scientific.Google Scholar
  29. 29.
    Dinkelbach, W. (1967). On nonlinear fractional programming. Management Science, 13(7), 492–498.MathSciNetCrossRefzbMATHGoogle Scholar
  30. 30.
    Neely, M. J. (2013). Dynamic optimization and learning for renewal systems. IEEE Transactions on Automatic Control, 58(1), 32–46.MathSciNetCrossRefzbMATHGoogle Scholar
  31. 31.
    Boyd, S., & Vandenberghe, L. (2004). Convex optimization. Cambridge: Cambridge University Press.CrossRefzbMATHGoogle Scholar
  32. 32.
    Neely, M. (2010). Stochastic network optimization with application to communication and queueing systems. San Rafael: Morgan and Claypool.CrossRefzbMATHGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.State Key Laboratory of ISN, School of Telecommunications Engineering, and Collaborative Innovation Center of Information Sensing and UnderstandingXidian UniversityXi’anChina

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