Composite vector quantization for optimizing antenna locations

Zekeriya Uykan*, Riku Jäntti

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

125 Downloads (Pure)


In this paper, we study the location optimization problem of remote antenna units (Raus) in generalized distributed antenna systems (GDASs). We propose a composite vector quantization (CVQ) algorithm that consists of unsupervised and supervised terms for Rau location optimization. We show that the CVQ can be used i) to minimize an upper bound to the cell-averaged SNR error for a desired/demanded location-specific SNR function, and ii) to maximize the cell-averaged effective SNR. The CVQ-DAS includes the standard VQ, and thus the well-known squared distance criterion (SDC) as a special case. Computer simulations confirm the findings and suggest that the proposed CVQ-DAS outperforms the SDC in terms of cell-averaged “effective SNR”.

Original languageEnglish
Pages (from-to)1225-12335
Number of pages11111
JournalTurkish Journal of Electrical Engineering and Computer Sciences
Issue number3
Publication statusPublished - 30 May 2018
MoE publication typeA1 Journal article-refereed


  • Antenna allocation problem
  • Clustering
  • Distributed antenna system
  • Squared distance criterion


Dive into the research topics of 'Composite vector quantization for optimizing antenna locations'. Together they form a unique fingerprint.

Cite this