Tytuł:

Designing Smart Antennas Using Machine Learning Algorithms, Journal of Telecommunications and Information Technology, 2023, nr 4

Tytuł publikacji grupowej:

2023, nr 4, JTIT-artykuły

Autor:

Samantaray, Barsa ; Das, Kunal Kumar ; Roy, Jibendu Sekhar

Temat i słowa kluczowe:

artificial neural networks ; decision tree ; ensemble algorithm ; machine learning ; smart antenna ; support vector machine

Abstrakt:

Smart antenna technologies improve spectral efficiency, security, energy efficiency, and overall service quality in cellular networks by utilizing signal processing algorithms that provide radiation beams to users while producing nulls for interferers. In this paper, the performance of such ML solutions as the support vector machine (SVM) algorithm, the artificial neural network (ANN), the ensemble algorithm (EA), and the decision tree (DT) algorithm used for forming the beam of smart antennas are compared. A smart antenna array made up of 10 half-wave dipoles is considered. The ANN method is better than the remaining approaches when it comes to achieving beam and null directions, whereas EA offers better performance in terms of reducing the side lobe level (SLL). The maximum SLL is achieved using EA for all the user directions. The performance of the ANN algorithm in terms of forming the beam of a smart antenna is also compared with that of the variable-step size adaptive algorithm.

Numer:

4

Wydawca:

Instytut Łączności - Państwowy Instytut Badawczy

Data wydania:

2023

Typ zasobu:

artykuł

DOI:

doi.org/10.26636/jtit.2023.4.1329

ISSN:

1509-4553

eISSN:

1899-8852

Źródło:

Journal of Telecommunications and Information Technology

Język:

ang

Licencja:

CC BY 4.0

Właściciel praw:

Instytut Łączności - Państwowy Instytut Badawczy