UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Ultra Dense Edge Caching Networks With Arbitrary User Spatial Density

Gruppi, E; Wong, K-K; Bocus, MZ; Chin, WH; (2020) Ultra Dense Edge Caching Networks With Arbitrary User Spatial Density. IEEE Transactions on Wireless Communications , 19 (7) pp. 4363-4377. 10.1109/TWC.2020.2983013. Green open access

[thumbnail of emanuele-Paper-TW-May-19-0557.R2.pdf]
Preview
Text
emanuele-Paper-TW-May-19-0557.R2.pdf - Accepted Version

Download (808kB) | Preview

Abstract

Cache-enabled small cells can be an effective solution to deliver contents to mobile users with much lower power and latency. While the trend for getting smaller and denser cells is clear, interference will soon become unmanageable and an obstacle when the number of content requests is massive. Moreover, content request is seldom a spatially homogeneous process due to physical impediments (e.g., buidings) and social activities, which makes resource allocation for content delivery more challenging. In this paper, we consider an ultra-dense network (UDN) in which content requests are served by cache-enabled access nodes which can either be active for delivering contents to users, or inactive to reduce interference and network energy consumption. Our aim is to devise an approach that can locally adapt the caching node density and content caching probabilities to accommodate any arbitrary user density and content request for maximizing the network’s successful content delivery probability (SCDP). With a non-homogeneous spatial distribution for user equipments (UEs), we find that user-load, a parameter at the access node, plays a major role in the overall optimization. Simulation results illustrate that the proposed method can obtain superior performance against the considered benchmarks, with up to 150-160% increase, and our optimized solutions effectively adapt to the spatial-dependent user density.

Type: Article
Title: Ultra Dense Edge Caching Networks With Arbitrary User Spatial Density
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TWC.2020.2983013
Publisher version: https://doi.org/10.1109/TWC.2020.2983013
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Content caching, heterogeneous network, small cell, stochastic geometry, ultra dense network
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10106697
Downloads since deposit
125Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item