Tytuł:

Machine Learning-Based Small Cell Location Selection Process, Journal of Telecommunications and Information Technology, 2021, nr 2

Autor:

Kułacz, Łukasz ; Wasilewska, Małgorzata

Temat i słowa kluczowe:

base station selection ; k-means clustering ; user equipment allocation ; spectra clustering

Opis:

In this paper, the authors present an algorithm for determining the location of wireless network small cells in a dense urban environment. This algorithm uses machine learning, such as k-means clustering and spectral clustering, as well as a very accurate propagation channel created using the ray tracing method. The authors compared two approaches to the small cell location selection process – one based on the assumption that end terminals may be arbitrarily assigned to stations, and the other assuming that the assignment is based on the received signal power. The mean bitrate values are derived for comparing different scenarios. The results show an improvement compared with the baseline results. This paper concludes that machine learning algorithms may be useful in terms of small cell location selection and also for allocating users to small cell base stations

Wydawca:

National Institute of Telecommunications

Data wydania:

2021, nr 2

Typ zasobu:

artykuł

Format:

application/pdf

Identyfikator zasobu:

ISSN 1509-4553, on-line: ISSN 1899-8852

Źródło:

Journal of Telecommunications and Information Technology

Język:

ang

Prawa:

Biblioteka Naukowa Instytutu Łączności