An Efficient Stochastic Gradient Descent Algorithm to Maximize the Coverage of Cellular Networks

Network coverage and capacity optimization is an important operational task in cellular networks. The network coverage maximization by adjusting azimuths and tilts of antennas is focused and the existing approaches are mainly gradient-free methods. A standard gradient descent algorithm and its impro...

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Veröffentlicht in:	IEEE transactions on wireless communications Jg. 18; H. 7; S. 3424 - 3436
Hauptverfasser:	Liu, Yaxi, Huangfu, Wei, Zhang, Haijun, Long, Keping
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.07.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Antennas Azimuth Base stations Cellular communication Cellular network Cellular networks computational complexity coverage optimization gradient descent Heuristic methods Linear programming Machine learning algorithms Optimization stochastic gradient descent
ISSN:	1536-1276, 1558-2248
Online-Zugang:	Volltext
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