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Dynamic Optimization of Generalized Least Squares Handover Algorithms
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0001-9810-3478
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
2014 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 13, no 3, 1235-1249 p.Article in journal (Refereed) Published
Abstract [en]

Efficient handover algorithms are essential for highly performing mobile wireless communications. 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. First, a new modeling of the handover process by a hybrid system that takes as input the handover parameters is established. Then, this hybrid system is used to pose some dynamical optimization approaches 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. Based on these approximations, a new approach to the solution of the handover optimizations is proposed. A distributed optimization algorithm is then developed to maximize handover performance. From an extensive set of results obtained by numerical computations and simulations, it is shown that the proposed algorithm improves performance of the handover considerably when compared to more traditional approaches.

Place, publisher, year, edition, pages
2014. Vol. 13, no 3, 1235-1249 p.
Keyword [en]
Handover, optimization, channel estimation, hybrid systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-117707DOI: 10.1109/TWC.2014.013014.121720ISI: 000333538100008Scopus ID: 2-s2.0-84897913353OAI: oai:DiVA.org:kth-117707DiVA: diva2:602658
Funder
Swedish Research Council
Note

QC 20140505. Updated from submitted to published.

Available from: 2013-02-02 Created: 2013-02-02 Last updated: 2017-12-06Bibliographically approved

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Fischione, Carlo

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