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BS sleeping strategy for energy-delay tradeoff in wireless-backhauling UDN

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Abstract

Ultra-dense network (UDN) has been recognized as a promising technology for 5G. Although turning off low-load base stations (BSs) can improve energy efficiency, it may cause degradation of delay performance. This makes energy-delay tradeoff (EDT) an important topic. In this paper, a theoretical framework for EDT, in wireless-backhauling UDN, is developed. First, we investigate association probabilities of UEs and transmission probabilities of BSs. Expressions for energy consumption and network packet delay are obtained and the impact that BS sleeping ratio has on energy consumption and packet delay are analyzed. Then, we formulate the EDT problem as a cost minimization problem to select the optimal set of sleeping small cells. To solve the EDT optimization problem, a locally optimal sleeping ratio for EDT is obtained using the dynamic gradient iteration algorithm and we prove that it can converge to the global optimal sleeping ratio. Then, queue-aware and channel-queue-aware sleeping strategies are proposed to find the optimal set of sleeping small cells according to the optimal sleeping ratio. We then see that the simulation and numerical results confirm the effectiveness of the proposed sleeping schemes.

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References

  1. 1

    You X H, Pan Z W, Gao X Q, et al. The 5G mobile communication: the development trends and its emerging key techniques (in Chinese). Sci Sin Inform, 2014, 44: 551–563

  2. 2

    Ismail M, Zhuang W H. Network cooperation for energy saving in green radio communications. IEEE Wirel Commun, 2011, 18: 76–81

  3. 3

    Wu J J, Zhang Y J, Zukerman M, et al. Energy-efficient base-stations sleep-mode techniques in green cellular networks: a survey. IEEE Commun Surv Tut, 2015, 17: 803–826

  4. 4

    Ge X H, Cheng H, Guizani M, et al. 5G wireless backhaul networks: challenges and research advances. IEEE Netw, 2014, 28: 6–11

  5. 5

    Suarez L, Bouraoui M A, Mertah M A, et al. Energy efficiency and cost issues in backhaul architectures for high data-rate green mobile heterogeneous networks. In: Proceedings of the 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Hong Kong, 2015. 1563–1568

  6. 6

    Tombaz S, Monti P, Farias F, et al. Is backhaul becoming a bottleneck for green wireless access networks? In: Proceedings of International Conference on Communications (ICC), Sydney, 2014. 4029–4035

  7. 7

    Chang P L, Miao G W. Joint optimization of base station deep-sleep and DTX micro-sleep. In: Proceedings of IEEE Global Communication Conference Workshops (Globecom Workshops), Washington, 2017

  8. 8

    Ebrahim A, Alsusa E. Interference and resource management through sleep mode selection in heterogeneous networks. IEEE Trans Commun, 2017, 65: 257–269

  9. 9

    Li Z H, Grace D, Mitchell P. Traffic-aware cell management for green ultradense small-cell networks. IEEE Trans Veh Technol, 2016, 66: 2600–2614

  10. 10

    Samarakoon S, Bennis M, Saad W, et al. Opportunistic sleep mode strategies in wireless small cell networks. In: Proceedings of IEEE International Conference on Communications (ICC), Sydney, 2016. 2707–2712

  11. 11

    Wu J, Liu J, Zhao H. Dynamic small cell on/off control for green ultra-dense networks. In: Proceedings of IEEE International Conference on Wireless Communications and Signal Processing (WCSP), Yangzhou, 2016

  12. 12

    Zhang Q, Yang C Y, Haas H, et al. Energy efficient downlink cooperative transmission with BS and antenna switching off. IEEE Trans Wirel Commun, 2014, 13: 5183–5195

  13. 13

    Liu C, Natarajan B, Xia H X. Small cell base station sleep strategies for energy efficiency. IEEE Trans Veh Technol, 2016, 65: 1652–1661

  14. 14

    Liu B, Zhao M, Zhou W Y, et al. Flow-level-delay constrainted small cell sleeping with macro base station cooperation for energy saving in hetnet. In: Proceedings of IEEE Vehicular Technology Conference (VTC-Fall), Boston, 2015

  15. 15

    Son K, Kim H, Yi Y, et al. Base station operation and user association mechanisms for energy-delay tradeoffs in green cellular networks. IEEE J Sel Areas Commun, 2011, 29: 1525–1536

  16. 16

    Li P, Jiagn H L, Pan Z W, et al. Energy-delay tradeoff in ultra-dense networks considering BS sleeping and cell association. IEEE Trans Veh Technol, 2018, 67: 734–751

  17. 17

    Nie G F, Tian H, Ren C S. Energy efficient cell selection in small cell networks with constrained backhaul links. IEEE Commun Lett, 2016, 20: 1199–1202

  18. 18

    Liu H, Zhang H J, Cheng J L, et al. Energy efficient power allocation and backhaul design in heterogeneous small cell networks. In: Proceedings of IEEE International Conference on Communications (ICC), Kuala Lumpur, 2016. 22–27

  19. 19

    Nie G F, Tian H, Sengul C, et al. Forward and backhaul link optimization for energy efficient OFDMA small cell networks. IEEE Trans Wirel Commun, 2016, 16: 1080–1093

  20. 20

    Zhang G Z, Quek T, Huang A, et al. Backhaul-aware base station association in two-tier heterogeneous cellular networks. In: Proceedings of the 16th International Workshop on Signal Processing Advances inWireless Communications (SPAWC), Stockholm, 2015. 390–394

  21. 21

    Han T, Ansari N. User association in backhaul constrained small cell networks. In: Proceedings of IEEE Wireless Communication and Networking Conference (WCNC), New Orleans, 2015. 1637–1642

  22. 22

    Jamali V, Michalopoulos D S, Uysal M, et al. Link allocation for multiuser systems with hybrid RF/FSO backhaul: delay-limited and delay-tolerant designs. IEEE Trans Wirel Commun, 2016, 15: 3281–3295

  23. 23

    Cui Z Y, Cui Q M, Zheng W, et al. Energy-delay analysis for partial spectrum sharing in heterogeneous cellular networks with wired backhaul. In: Proceedings of IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Valencia, 2016. 1563–1568

  24. 24

    Auer G, Giannini V, Desset C, et al. How much energy is needed to run a wireless network? IEEE Trans Wirel Commun, 2011, 18: 40–49

  25. 25

    Jo H S, Sang Y J, Xia P, et al. Heterogeneous cellular networks with flexible cell association: a comprehensive downlink SINR analysis. IEEE Trans Wirel Commun, 2012, 11: 3484–3495

  26. 26

    Haenggi M, Andrews J G, Baccelli F, et al. Stochastic geometry and random graphs for the analysis and design of wireless networks. IEEE J Sel Areas Commun, 2009, 27: 1029–1046

  27. 27

    Li X, Ji H, Wang K, et al. Energy-efficient access scheme with joint consideration on backhualing in UDN. In: Proceedings of IEEE Vehicular Technology Conference (VTC-Fall), Montreal, 2016

  28. 28

    Takagi H. Queueing Analysis: A Foundation of Performance Evaluation, Volume I: Vacation and Priority Systems. 1st ed. Amsterdam: Elsevier, 1991

  29. 29

    Li L, Peng M G, Yang C Q, et al. Optimization of base station density for high energy efficient cellular networks with sleeping strategies. IEEE Trans Veh Technol, 2016, 65: 7501–7514

  30. 30

    Stephen B, Lieven V. Convex Optimization. 1st ed. Cambridge: Cambridge University Press, 2009

  31. 31

    Jo H S, Xia P, Andrews J G. Open, closed, and shared access femtocells in the downlink. J Wirel Commun Netw, 2012, 2012: 363–378

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Acknowledgements

This work was partially supported by National Major Project (Grant No. 2017ZX03001002-004), National Natural Science Foundation Project (Grant No. 61521061), 333 Program of Jiangsu (Grant No. BRA2017366), and Huawei Technologies Co., Ltd.

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Correspondence to Zhiwen Pan.

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Li, P., Shen, Y., Sahito, F. et al. BS sleeping strategy for energy-delay tradeoff in wireless-backhauling UDN. Sci. China Inf. Sci. 62, 42303 (2019). https://doi.org/10.1007/s11432-018-9494-9

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Keywords

  • ultra-dense networks
  • sleeping ratio
  • sleeping strategy
  • wireless backhaul
  • energy-delay tradeoff