Learned-SBL-GAMP based hybrid precoders/combiners in millimeter wave massive MIMO systems

In Millimeter-Wave (mm-Wave) massive Multiple-Input Multiple-Output (MIMO) systems, hybrid precoders/combiners must be designed to improve antenna gain and reduce hardware complexity. Sparse Bayesian learning via Expectation Maximization (SBL-EM) algorithm is not practically feasible for high signal...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	PloS one Jg. 18; H. 9; S. e0289868
Hauptverfasser:	Ali K., Shoukath, Khan, Arfat Ahmad, T, Perarasi, Ur Rehman, Ateeq, Ouahada, Khmaies
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	San Francisco Public Library of Science 08.09.2023 Public Library of Science (PLoS)
Schlagworte:	Accuracy Algorithms Analysis Antenna gain Antennas Antennas (Electronics) Artificial neural networks Bayesian analysis Biology and Life Sciences Communication Complexity Computer and Information Sciences Computer applications Deep learning Efficiency Engineering and Technology Hybrid systems Information management Machine learning Matched pursuit Matching Mean square errors Medicine and Health Sciences Message passing Millimeter waves MIMO communication MIMO communications Neural networks Optimization Physical Sciences Research and Analysis Methods Training India
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!