A Deep Constrained and Synchronous Training Framework for Hybrid Precoding

To reduce the computational complexity and improve the achievable rate of hybrid precoding, we propose a deep constrained and synchronous training framework, which enables effective learning from the fully digital precoders and approaches the upper bound performance. The key innovation focuses on in...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE communications letters Jg. 26; H. 6; S. 1288 - 1292
Hauptverfasser:	Liu, Zijian, Luo, Yang, Xu, Yan, Luo, Chunbo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.06.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Array signal processing efficiency fully digital precoder Hybrid power systems Hybrid precoding Neural networks Precoding Propagation losses Radio frequency residual precoding network spectral synchronous training Training Upper bounds
ISSN:	1089-7798, 1558-2558
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!