SCIENCE CHINA Information Sciences, Volume 60, Issue 4: 042303(2017) https://doi.org/10.1007/s11432-016-0249-9

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

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  • ReceivedJul 15, 2016
  • AcceptedAug 11, 2016
  • PublishedNov 16, 2016


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.

Funded by

Hong Kong Macao and Taiwan Science and Technology Cooperation Projects(2014DFT10320)

Beijing Nova Program(xx2012037)

National Natural Science Foundation of China(61471058)

International Cooperation NSFC Program(61461136002)



This work was supported by National Natural Science Foundation of China (Grant No. 61471058), Beijing Nova Program (Grant No. xx2012037), International Cooperation NSFC Program (Grant No. 61461136002), and Hong Kong, Macao and Taiwan Science and Technology Cooperation Projects (Grant No. 2014DFT10320).


[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 Google Scholar

[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 CrossRef Google Scholar

[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: 10-103 Google Scholar

[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: 082305-103 Google Scholar

[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 CrossRef Google Scholar

[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 CrossRef Google Scholar

[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. Google Scholar

[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 CrossRef Google Scholar

[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 CrossRef Google Scholar

[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 CrossRef Google Scholar

[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 CrossRef Google Scholar

[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 CrossRef Google Scholar

[13] Koutitas G, Karousos A, Tassiulas L. Deployment strategies and energy efficiency of cellular networks. IEEE Trans Wirel Commun, 2012, 11: 2552-2563 CrossRef Google Scholar

[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 Google Scholar

[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. Google Scholar

[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 Google Scholar

[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 CrossRef Google Scholar

[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 CrossRef Google Scholar

[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 Google Scholar

[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 CrossRef Google Scholar

[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 CrossRef Google Scholar

[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 CrossRef Google Scholar

[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 CrossRef Google Scholar

[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 Google Scholar

[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 CrossRef Google Scholar

[26] Singh S, Jeffrey G A. Joint resource partitioning and offloading in heterogeneous cellular networks. IEEE Trans Wirel Commun, 2014, 13: 888-901 CrossRef Google Scholar

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