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Good Neighbor Distributed Beam Scheduling in Coexisting Multi-RAT Networks

Kuzminskiy, Alexandr, Xiao, Pei and Tafazolli, Rahim (2018) Good Neighbor Distributed Beam Scheduling in Coexisting Multi-RAT Networks In: IEEE Wireless Communications and Networking Conference 2018, 15 - 18 April 2018, Barcelona, Catalonia.

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Abstract

Spectrum sharing and employing highly directional antennas in the mm-wave bands are considered among the key enablers for 5G networks. Conventional interference avoidance techniques like listen-before-talk (LBT) may not be efficient for such coexisting networks. In this paper, we address a coexistence mechanism by means of distributed beam scheduling with minimum cooperation between spectrum sharing subsystems without any direct data exchange between them. We extend a “Good Neighbor” (GN) principle initially developed for decentralized spectrum allocation to the distributed beam scheduling problem. To do that, we introduce relative performance targets, develop a GN beam scheduling algorithm, and demonstrate its efficiency in terms of performance/complexity trade off compared to that of the conventional selfish (SLF) and recently proposed distributed learning scheduling (DLS) solutions by means of simulations in highly directional antenna mm-wave scenarios.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Kuzminskiy, Alexandra.kuzminskiy@surrey.ac.uk
Xiao, PeiP.Xiao@surrey.ac.uk
Tafazolli, RahimR.Tafazolli@surrey.ac.uk
Date : 26 April 2018
Copyright Disclaimer : © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Depositing User : Melanie Hughes
Date Deposited : 26 Jan 2018 10:10
Last Modified : 18 Apr 2018 02:08
URI: http://epubs.surrey.ac.uk/id/eprint/845695

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