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5 - Dense networks of small cells

Published online by Cambridge University Press:  05 December 2015

Jialing Liu
Affiliation:
Huawei R&D
Weimin Xiao
Affiliation:
Huawei R&D
Anthony C. K. Soong
Affiliation:
Huawei R&D
Alagan Anpalagan
Affiliation:
Ryerson Polytechnic University, Toronto
Mehdi Bennis
Affiliation:
University of Oulu, Finland
Rath Vannithamby
Affiliation:
Intel Corporation, Portland, Oregon
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Summary

Introduction

During the last few years, wireless data traffic has skyrocketed, driven mainly by a large penetration of smart phones and devices. In 2013, an exabyte of data traveled across the global mobile network monthly [1]. By 2020, data traffic served by such networks is expected to increase by up to a factor of 100, including traffic generated by the widespread adoption of device–device (D2D) and the Internet of Things (IoT) connected via machine–machine (M2M) communications. It is widely recognized that this general trend toward more explosive growth may accelerate even further in future, and how to meet such a demand has been one of the most active and rapidly growing areas in the wireless communication community in the past decade in terms of both academic and industrial research and development [2].

Facing the unprecedented challenge, the wireless communication community has considered many candidate solutions. A significant portion of these are focused on increasing the communication resources, e.g., deploying more network nodes, which leads to densification of existing networks, utilizing wider bandwidth, increasing antenna numbers, and employing additional resources to offload. Among them, the dense network approach stands out for its high scalability of providing magnitudes of capacity increase. Extensive research has been devoted to dense networks (see e.g., [3–8] and references therein).

Indeed, commercial wireless networks are already becoming denser and dense-network deployment will be a critical factor (together with other solutions) to meet the ever-increasing traffic demand. The trends for traffic and network-density growth over a 20-year span are illustrated in Figure 5.1.

In Figure 5.1, the network densities for the years 2000 to 2015 were estimated from 3GPP publications (e.g., [3, 9], etc.), whereas the network density for year 2020 is a projection based on historic data and recent trends. In more detail, around year 2000, sparse 3G network deployments of macro base stations covered wide areas with typical cell radii of several kilometers. Starting from around 2005, the network density increased to about 10 to 20 nodes/km2 and cell radii shrunk to between one kilometer and several hundreds of meters, according to the study in 3GPP LTE Rel-8/9; however, macro eNBs (evolved NodeB, also known as base stations, BS, BTS, etc.) were still the main focus.

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Publisher: Cambridge University Press
Print publication year: 2015

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References

[1] 4G Americas, “Mobile broadband explosion: the 3GPP wireless evolution,” 4G Americas white paper, www.4gamericas.org, Aug. 2013.
[2] Cavalcanti, D., Agrawal, D., Cordeiro, C., Xie, B., and Kumar, A., “Issues in integrating cellular networks WLANs, and MANETs: a futuristic heterogeneous wireless network,” IEEE Wireless Communications, 12, 30–41, June 2005.CrossRefGoogle Scholar
[3] 3GPP TR 36.932, “Study on scenarios and requirements of LTE small cell enhancements,” v0.2.0, Nov. 2012.
[4] Kang, D. H., Sung, K. W., and Zander, J., “Cost efficient high capacity indoor wireless access: denser Wi-Fi or coordinated pico-cellular?” http://arxiv.org/pdf/1211.4392, Nov. 2012.
[5] Ling, J. and Chizhik, D., “Capacity scaling of indoor pico-cellular networks via reuse,” IEEE Communications Letters, 16:2, Feb. 2012.CrossRefGoogle Scholar
[6] Dhillon, H. S., Ganti, R. K., Baccelli, F., and Andrew, J. G., “Modeling and analysis of K-Tier downlink heterogeneous cellular networks,” IEEE Journal on Selected Areas in Communications, 30, 550–560, April 2012.CrossRefGoogle Scholar
[7] 3GPP TR 36.872, “Small cell enhancements for E-UTRAN – physical layer aspects,” v12.1.0, Dec. 2013.
[8] 4G Americas, “Developing and integrating a high performance Het-Net,” 4G Americas white paper, www.4gamericas.org, Oct. 2012.
[9] 3GPP TR36.814, “Further advancements for E-UTRA physical layer aspects,” 2010.
[10] IST-WINNER D1.1.2 P. Kyösti, et al., “WINNER II Channel Models”, ver 1.1, Sept. 2007. Available: www.ist-winner.org/WINNER2-Deliverables/D1.1.2v1.1.pdf.
[11] Baccelli, F. and Blaszczyszyn, B., “Stochastic geometry and wireless networks,” Foundations and Trends in Networking, 2010.
[12] Haenggi, M., Stochastic Geometry for Wireless Networks. Cambridge University Press, 2012.CrossRefGoogle Scholar
[13] Zhuang, B., Guo, D., and Honig, M. L., “Energy management of dense wireless heterogeneous networks over slow timescales,” In Communication, Control, and Computing (Allerton), 2012 50th Annual Allerton Conference, pp. 26–32, IEEE, 2012.
[14] Dhillon, H. S., Ganti, R. K., and Andrews, J. G., “Load-aware modeling and analysis of heterogeneous cellular networks,” CoRR, vol. abs/1204.1091, 2012.Google Scholar

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