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Beam-centric Handover Decision in Dense 5G-mmWave Networks

Kose, Abdulkadir, Foh, Chuan Heng, Lee, Haeyoung and Dianati, Mehrdad (2020) Beam-centric Handover Decision in Dense 5G-mmWave Networks In: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 31 Aug - 1 Sept 2020, London, UK (moved to Virtual Conference).

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Abstract

In 5G network, dense deployment and millimetre wave (mmWave) are some of the key approaches to boost network capacity. Dense deployment of mmWave small cells using narrow directional beams will escalate the cell and beam related handovers for high mobility of vehicles, which may in turn limits the performance gain promised by 5G. One of the research issues in mmWave handover is to minimise the handover needs by identifying long lasting connections. In this paper, we first develop an analytical model to derive the vehicle sojourn time within a beam coverage. When multiple connections offered by nearby all mmWave small cells are available when upon a handover event, we further derive the longest sojourn time among all potential connections which represents the theoretical upperbound limit of the sojourn time performance. We then design a Fuzzy Logic (FL) based distributed beam-centric handover decision algorithm to maximise vehicle sojourn time. Simulation experiments are conducted to validate our analytical model and show the performance advantage of our proposed FLbased solution when compared with commonly used approach of connecting to the strongest connection.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Kose, Abdulkadira.kose@surrey.ac.uk
Foh, Chuan Heng
Lee, Haeyounghaeyoung.lee@surrey.ac.uk
Dianati, Mehrdad
Date : 19 June 2020
Funders : Jaguar Land Rover, EPSRC, University of Surrey 5GIC
Grant Title : EPSRC Grant
Uncontrolled Keywords : Beam Handover, mmWave Networks, 5G.
Depositing User : James Marshall
Date Deposited : 25 Jun 2020 15:22
Last Modified : 17 Jul 2020 09:50
URI: http://epubs.surrey.ac.uk/id/eprint/858062

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