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Globally Optimal Base Station Clustering in Interference Alignment-Based Multicell Networks
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-7724-5896
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0003-0995-9835
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-3599-5584
2016 (English)In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 23, no 4, 512-516 p.Article in journal (Refereed) Published
Abstract [en]

Coordinated precoding based on interference alignment is a promising technique for improving the throughputs in future wireless multicell networks. In small networks, all base stations can typically jointly coordinate their precoding. In large networks however, base station clustering is necessary due to the otherwise overwhelmingly high channel state information (CSI) acquisition overhead. In this work, we provide a branch and bound algorithm for finding the globally optimal base station clustering. The algorithm is mainly intended for benchmarking existing suboptimal clustering schemes. We propose a general model for the user throughputs, which only depends on the long-term CSI statistics. The model assumes intracluster interference alignment and is able to account for the CSI acquisition overhead. By enumerating a search tree using a best-first search and pruning sub-trees in which the optimal solution provably cannot be, the proposed method converges to the optimal solution. The pruning is done using specifically derived bounds, which exploit some assumed structure in the throughput model. It is empirically shown that the proposed method has an average complexity which is orders of magnitude lower than that of exhaustive search.

Place, publisher, year, edition, pages
IEEE , 2016. Vol. 23, no 4, 512-516 p.
Keyword [en]
Base station clustering, branch and bound, interference alignment
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-184176DOI: 10.1109/LSP.2016.2536159ISI: 000373023600002Scopus ID: 2-s2.0-84964389846OAI: oai:DiVA.org:kth-184176DiVA: diva2:915435
Note

QC 20160405

Available from: 2016-03-30 Created: 2016-03-30 Last updated: 2017-11-30Bibliographically approved

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Brandt, RasmusRami, MochaourabBengtsson, Mats

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