Springer Nature is making Coronavirus research free. View research | View latest news | Sign up for updates

Energy-aware deployment of dense heterogeneous cellular networks with QoS constraints

基于能效的密集异构蜂窝网络部署研究

  • 112 Accesses

  • 5 Citations

Abstract

The base station (BS) configuration is a key factor to improve energy efficiency (EE). In this paper, we focus on designing the network deployment parameters (i.e., BS densities) for biased K-tier heterogeneous cellular network (HCN) with quality of service (QoS) provisioning. Using appropriate approximations, we derive the closed-form expressions of optimal BS density across all tiers to minimize the area power consumption (APC) by applying the stochastic geometry theory, while satisfying the users’ QoS requirements. These results are used to obtain some new insights into the EE performance of biased HCN deployment. With the aid of this approach, the best type of BSs to be deployed or switched off for energy saving purposes can be identified from the perspectives of BS transmission power. More precisely, if the BS transmission power ratio between an arbitrary pair of tiers of K-tier HCN, e.g., the small cell BS and macro BS tiers, is higher than a threshold which is a function of path loss exponent, bias factor and power consumption, the small cell BSs are preferred. The opposite situation takes place otherwise. Furthermore, it is also shown that, compared to the unbiased HCN scenario, significant energy savings are possible by appropriately biasing the HCN and optimizing the BS density, subject to the QoS constraints among all tiers.

抽象

摘要

本文从全网角度研究任意K层偏置异构蜂窝网络部署问题, 基于随机几何数学理论推导出在满足每一层网络中用户速率覆盖需求的约束下最小化网络能耗的基站部署密度闭式解, 进一步得出能效最优的基站部署类型。当K层异构网络中任意两层(例如第i层和第j层)的基站发射功率之比大于特定门限(与路损因子、偏置因子及基站功耗相关)时, 尽可能多的部署第i层基站, 关闭第j层基站, 优化的基站部署密度由闭式解得到。反之则优化的部署策略相反。相比于非偏置异构网络, 偏置异构网络通过合理的设置偏置因子可以显著节能。

创新点

在满足每一层网络用户速率覆盖需求的约束条件下, 研究基于能效的任意K层偏置异构网络的最优部署策略。

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

References

  1. 1

    Ma Z, Zhang Z Q, Ding Z G, et al. Key techniques for 5G wireless communications: network architecture, physical layer, and MAC layer perspectives. Sci China Inf Sci, 2015, 58: 041301

  2. 2

    Cui Q M, Wang H, Hu P X, et al. Evolution of limited feedback CoMP systems from 4G to 5G. IEEE Veh Tech Mag, 2014, 9: 94–103

  3. 3

    Liu Y J, Lu L, Geoffrey L, et al. Joint user association and spectrum allocation for small cell networks with wireless backhauls. IEEE Wirel Commun Lett, 2016, doi: 10.1109/LWC.2016.2593465

  4. 4

    Fei Z S, Ding H C, Xing C W, et al. Performance analysis for range expansion in heterogeneous networks. Sci China Inf Sci, 2014, 57: 082305

  5. 5

    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

  6. 6

    Singh S, Dhillon H S, Andrews J G. Offloading in heterogeneous networks: modeling, analysis, and design insights. IEEE Trans Wirel Commun, 2013, 12: 2484–2497

  7. 7

    Fettweis G, Zimmermann E. ICT energy consumption-trends and challenges. In: Proceedings of the 11th International Symposium on Wireless Personal Multimedia Communications, Lapland, 2008. 8–11

  8. 8

    Hasan Z, Boostanimehr H, Bhargava V K. Green cellular networks: a survey, some research issues and challenges. IEEE Commun Surv Tut, 2011, 13: 524–540

  9. 9

    Fikadu M, Sofotasios P, Muhaidat S, et al. Error rate and power allocation analysis of regenerative networks over generalized fading channels. IEEE Trans Commun, 2016, 64: 1751–1768

  10. 10

    Zhou M, Cui Q M, Jantti R, et al. Energy-efficient relay selection and power allocation for two-way relay channel with analog network coding. IEEE Commun Lett, 2012, 16: 816–819

  11. 11

    Cui Q M, Yang X J, Jyri H, et al. Optimal energy-efficient relay deployment for the bidirectional relay transmission schemes. IEEE Trans Veh Tech, 2014, 63: 2625–2641

  12. 12

    Cui Q M, Huang X Q, Luo B, et al. Capacity analysis and optimal power allocation for coordinated transmission in MIMO-OFDM systems. Sci China Inf Sci, 2012, 55: 1372–1387

  13. 13

    Koutitas G, Karousos A, Tassiulas L. Deployment strategies and energy efficiency of cellular networks. IEEE Trans Wirel Commun, 2012, 11: 2552–2563

  14. 14

    Yunas S F, Valkama M, Niemela J. Spectral and energy efficiency of ultra-dense networks under different deployment strategies. IEEE Commun Mag, 2015, 53: 90–100

  15. 15

    Li L, Peng M G, Yang C Q, et al. Base station density optimization for high energy efficiency in two-tier cellular networks. In: Proceedings of IEEE Global Communications Conference, Austin, 2014. 1804–1809

  16. 16

    Li L, Peng M, Yang C Q, et al. Optimization of base station density for high energy efficient cellular networks with sleeping strategies. IEEE Trans Veh Tech, 2015, 65: 7501–7514

  17. 17

    Yong S S, Quek T Q S, Kountouris M, et al. Energy efficient heterogeneous cellular networks. IEEE J Sel Area Commun, 2013, 31: 840–850

  18. 18

    Wildemeersch M, Quek T Q S, Slump C H, et al. Cognitive small cell networks: energy efficiency and trade-offs. IEEE Trans Commun, 2013, 61: 4016–4029

  19. 19

    Yu P S, Lee J, Quek T, et al. Traffic Offloading in heterogeneous networks with energy harvesting personal cells-network throughput and energy efficiency. IEEE Trans Wirel Commun, 2015, 15: 1146–1161

  20. 20

    Du Q H, Zhang X. Statistical QoS provisionings for wireless unicast/multicast of multi-layer video streams. IEEE J Sel Area Commun, 2010, 28: 420–433

  21. 21

    Wu J, Zhou S, Niu Z S. Traffic-aware base station sleeping control and power matching for energy-delay tradeoffs in green cellular networks. IEEE Trans Wirel Commun, 2013, 12: 4196–4209

  22. 22

    Huang Y, Zhang X, Zhang J X, et al. Energy-efficient design in heterogeneous cellular networks based on large-scale user behavior constraints. IEEE Trans Wirel Commun, 2014, 13: 4746–4757

  23. 23

    Peng J L, Hong P L, Xue K P. Energy-aware cellular deployment strategy under coverage performance constraints. IEEE Trans Wirel Commun, 2015, 14: 69–80

  24. 24

    Cao D X, Zhou S, Niu Z S. Optimal combination of base station densities for energy-efficient two-tier heterogeneous cellular networks. IEEE Trans Wirel Commun, 2015, 53: 90–100

  25. 25

    Du Q H, Song H B, Xu Q, et al. Interference-controlled D2D routing aided by knowledge extraction at cellular infrastructure towards ubiquitous CPS. Pers Ubiquit Comput, 2015, 19: 1033–1043

  26. 26

    Singh S, Jeffrey G A. Joint resource partitioning and offloading in heterogeneous cellular networks. IEEE Trans Wirel Commun, 2014, 13: 888–901

Download references

Author information

Correspondence to Qimei Cui.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Cui, Q., Cui, Z., Zheng, W. et al. Energy-aware deployment of dense heterogeneous cellular networks with QoS constraints. Sci. China Inf. Sci. 60, 042303 (2017). https://doi.org/10.1007/s11432-016-0249-9

Download citation

Keywords

  • heterogeneous cellular networks
  • stochastic geometry
  • energy efficiency
  • BS density
  • energy saving

关键词

  • 异构蜂窝网络
  • 随机几何
  • 能效
  • 基站密度
  • 节能