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Utility-based resource management for future mobile communications considering QoE
Citation Link: https://doi.org/10.15480/882.2584
Publikationstyp
Doctoral Thesis
Date Issued
2016-12
Sprache
English
Author(s)
Herausgeber*innen
Advisor
Referee
Title Granting Institution
Technische Universität Hamburg-Harburg
Place of Title Granting Institution
Hamburg
Examination Date
2016-08-22
Institut
TORE-DOI
TORE-URI
First published in
Number in series
2
Citation
Zuerst veröffentlicht: 978-3-8440-4954-1
Publisher
Shaker
This work addresses the mobile networks, such as LTE (Long Term Evolution). The key objective is to improve the system performance in means of user satisfaction. Two main potential bottleneck links are identified, i.e. the Radio Interface and the transport network link from base station to core network.
Therefore, first a utility based radio scheduling algorithm is proposed. The scheduling algorithm, which maximizes the aggregated QoE, is proven to be optimal analytically. In a second step the resource limitation on the second bottleneck link, the S1 interface in the transport network is considered in addition. The mathematical problem is formulated considering the resource on both bottleneck link and maximizing the aggregated user satisfaction. The formulated problem is proven to be a convex optimization problem, and then solved using the Lagrangian relaxation method. In addition, computational advantageous heuristics are developed and compared in simulations against legacy approaches and the optimal solution.
Therefore, first a utility based radio scheduling algorithm is proposed. The scheduling algorithm, which maximizes the aggregated QoE, is proven to be optimal analytically. In a second step the resource limitation on the second bottleneck link, the S1 interface in the transport network is considered in addition. The mathematical problem is formulated considering the resource on both bottleneck link and maximizing the aggregated user satisfaction. The formulated problem is proven to be a convex optimization problem, and then solved using the Lagrangian relaxation method. In addition, computational advantageous heuristics are developed and compared in simulations against legacy approaches and the optimal solution.
Subjects
Mobile Communication
LTE
Resource Management
Scheduling
Convex Optimization
QoE
DDC Class
004: Informatik
380: Handel, Kommunikation, Verkehr
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