K-means clustering algorithm in antenna selection for Massive MIMO

Autor:	Lei Guowei, Xiao Xuefang, Lin Yun
Rok vydání:	2019
Předmět:	History Computer science MIMO k-means clustering Antenna (radio) Algorithm Selection (genetic algorithm) Computer Science Applications Education
Zdroj:	Journal of Physics: Conference Series. 1314:012061
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/1314/1/012061
Popis:	Massive multiple-input multiple-output (MIMO) is considered as the promising technique in next generation of wireless communication system. It has high spectral efficiency and energy efficiency. In addition, it can mitigate the interferences among users as the amount of antennas at base station (BS) grows. But, the high complexity and cost of hardware pose huge challenges to massive MIMO. In future, antenna selection (AS) is still a choice to decrease the burden of BS. In this letter, the AS algorithm based on K-means clustering is proposed to maximizing the capacity with low computational complexity. Finally, the simulated results are presented to validate the proposed method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::473a65732a463a4da6a97421fa16dcfa https://doi.org/10.1088/1742-6596/1314/1/012061 Zobrazit plný text záznamu