Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Dynamic optimization of generalized least squares handover algorithms
KTH, School of Electrical Engineering (EES), Automatic Control.
KTH, School of Electrical Engineering (EES), Automatic Control.
2017 (English)In: 2014 7th International Conference on Network Games, Control and Optimization, NetGCoop 2014, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 247-254, article id 7943424Conference paper (Refereed)
Abstract [en]

Efficient handover algorithms are essential for highly performing cellular networks. These algorithms depend on numerous parameters, whose settings must be appropriately optimized to offer a seamless connectivity. Nevertheless, such an optimization is difficult in a time varying context, unless adaptive strategies are used. In this paper, a new approach for the handover optimization is proposed. Three dynamical optimization approaches are presented, where the probability of outage and the probability of handover are considered. Since it is shown that these probabilities are difficult to compute, simple approximations of adequate accuracy are developed. A distributed optimization algorithm is then developed to maximize handover performance. Numerical results show that the proposed algorithm improves the performance of the handover considerably when compared to more traditional approaches.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 247-254, article id 7943424
Keywords [en]
Probability, Distributed optimization, Dynamic optimization, Generalized least square, Handover performance, Optimization approach, Probability of outage, Seamless connectivity, Traditional approaches, Optimization
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-212127Scopus ID: 2-s2.0-85022209721ISBN: 9788884435743 OAI: oai:DiVA.org:kth-212127DiVA, id: diva2:1133699
Conference
7th International Conference on Network Games, Control and Optimization, NetGCoop 2014, Trento, Italy, 29 October 2014 through 31 October 2014
Note

QC 20170816

Available from: 2017-08-16 Created: 2017-08-16 Last updated: 2017-08-16Bibliographically approved

Open Access in DiVA

No full text in DiVA

Scopus

Search in DiVA

By author/editor
Fischione, CarloAthanasiou, George
By organisation
Automatic Control
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 13 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf