Composite vector quantization for optimizing antenna locations

Authors

ZEKERİYA UYKAN
RIKU JANTTI

DOI

10.3906/elk-1512-245

Abstract

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 \textit{upper bound} to the cell-averaged SNR error for a desired/demanded location-specific SNR function, and ii) to maximize the cell-averaged \textit{effective} \textit{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''.

Keywords

Distributed antenna system, antenna allocation problem, clustering, squared distance criterion

First Page

1225

Last Page

1235

Recommended Citation

UYKAN, ZEKERİYA and JANTTI, RIKU (2018) "Composite vector quantization for optimizing antenna locations," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 26: No. 3, Article 9. https://doi.org/10.3906/elk-1512-245
Available at: https://journals.tubitak.gov.tr/elektrik/vol26/iss3/9