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Edge caching in dense heterogeneous cellular networks with massive MIMO aided self-backhaul

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posted on 17.08.2018, 13:12 by Lifeng Wang, Kai-Kit Wong, Sangarapillai Lambotharan, Arumugam Nallanathan, Maged Elkashlan
This paper focuses on edge caching in dense heterogeneous cellular networks (HetNets), in which small base stations (SBSs) with limited cache size store the popular contents, and massive multiple-input multiple-output (MIMO) aided macro base stations provide wireless self-backhaul when SBSs require the non-cached contents. Our aim is to address the effects of cell load and hit probability on the successful content delivery (SCD), and present the minimum required base station density for avoiding the access overload in an arbitrary small cell and backhaul overload in an arbitrary macrocell. The achievable rate of massive MIMO backhaul without any downlink channel estimation is derived to calculate the backhaul time, and the latency is also evaluated in such networks. The analytical results confirm that hit probability needs to be appropriately selected, in order to achieve SCD. The interplay between cache size and SCD is explicitly quantified. It is theoretically demonstrated that when non-cached contents are requested, the average delay of the non-cached content delivery could be comparable to the cached content delivery with the help of massive MIMO aided selfbackhaul, if the average access rate of cached content delivery is lower than that of self-backhauled content delivery. Simulation results are presented to validate our analysis

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School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Transactions on Wireless Communications

Citation

WANG, L. ... et al., 2018. Edge caching in dense heterogeneous cellular networks with massive MIMO aided self-backhaul. IEEE Transactions on Wireless Communications, 17 (9), pp.6360 - 6372.

Publisher

Institute of Electrical and Electronics Engineers (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

10/07/2018

Publication date

2018-08-02

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

1536-1276

Language

en

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