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Performance analysis of cache-enabled millimeter wave small cell networks

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posted on 2018-07-09, 11:06 authored by Yongxu Zhu, Gan Zheng, Kai-Kit Wong, Shi Jin, Sangarapillai LambotharanSangarapillai Lambotharan
CCBY Millimeter wave (mmWave) small-cell networks can provide high regional throughput, but the backhaul requirement has become a performance bottleneck. This paper proposes a hybrid system that combines traditional backhaul-connected small base stations (SBSs) and cache-enabled SBSs to achieve the maximum area spectral efficiency (ASE) while saving backhaul consumption in mmWave small cell networks. We derive and compare the ASE results for both the traditional and hybrid networks, and also show that the optimal content placement to maximize ASE is to cache the most popular contents. Numerical results demonstrate the performance improvement of deploying cache-enabled SBSs. Furthermore, given a total caching capacity, it is revealed that there is a tradeoff between the cache-enabled SBSs density and individual cache size to maximize the ASE.

Funding

This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/N007840/1 and EP/N008219/1. The work of S. Jin was supported by the National Natural Science Foundation of China under Grant 61531011.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Transactions on Vehicular Technology

Citation

ZHU, Y. ...et al., 2018. Performance analysis of cache-enabled millimeter wave small cell networks. IEEE Transactions on Vehicular Technology, 67 (7), pp.6695-6699.

Publisher

IEEE

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/

Acceptance date

2018-01-14

Publication date

2018

Notes

This is an Open Access Article. It is published by IEEE under the Creative Commons Attribution 3.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/

ISSN

0018-9545

Language

  • en

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