University of Surrey

Test tubes in the lab Research in the ATI Dance Research

A Context-Aware User-Driven Framework for Network Selection in 5G Multi-RAT environments

Bouali, F, Moessner, K and Fitch, M (2016) A Context-Aware User-Driven Framework for Network Selection in 5G Multi-RAT environments In: 2016 IEEE 84th Vehicular Technology Conference, 2016-09-18 - 2016-09-21, Montréal.

[img]
Preview
Text
Camera-ready VTC-Fall 2016.pdf - Accepted version Manuscript

Download (1MB) | Preview
[img]
Preview
Text (licence)
SRI_deposit_agreement.pdf
Available under License : See the attached licence file.

Download (33kB) | Preview
[img] Text
Updated_Paper_Faouzi.pdf - Accepted version Manuscript
Restricted to Repository staff only
Available under License : See the attached licence file.

Download (1MB)

Abstract

To improve inter-operability of future 5G systems with existing technologies, this paper proposes a novel context-aware user-driven framework for network selection in multi- RAT environments. It relies on fuzzy logic to cope with the lack of information usually associated with the terminal side and the intrinsic randomness of the radio environment. In particular, a fuzzy logic controller first estimates the out-of-context suitability of each RAT to support the QoS requirements of a set of heterogeneous applications. Then, a fuzzy multiple attribute decision making (MADM) methodology is developed to combine these estimates with the various components of the context (e.g., terminal capabilities, user preferences and operator policies) to derive the in-context suitability level of each RAT. Based on this novel metric, two spectrum selection and spectrum mobility functionalities are developed to select the best RAT in a given context. The proposed fuzzy MADM approach is validated in a dense small cell environment to perform a context-aware offloading for a mixture of delay-sensitive and best-effort applications. The results reveal that the fuzzy logic component is able to efficiently track changes in the operating conditions of the different RATs, while the MADM component enables to implement an adjustable context-aware strategy. The proposed fuzzy MADM approach results in a significant improvement in achieving the target strategy, while maintaining an acceptable QoS level compared to a traditional offloading based on signal strength.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
AuthorsEmailORCID
Bouali, FUNSPECIFIEDUNSPECIFIED
Moessner, KUNSPECIFIEDUNSPECIFIED
Fitch, MUNSPECIFIEDUNSPECIFIED
Date : 2016
Copyright Disclaimer : This paper has been accepted for inclusion in the 2016 IEEE 84th Vehicular Technology Conference in Montreal © 2016 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.
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 06 Jul 2016 15:00
Last Modified : 10 Nov 2016 09:23
URI: http://epubs.surrey.ac.uk/id/eprint/811134

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800