Learning-Based Constellation Design for Uplink Bi-Static Integrated Sensing and Communication

This paper proposes an end-to-end deep learning based constellation design for integrated sensing and communication (ISAC) for the uplink of orthogonal frequency division multiplexing (OFDM) systems. Utilizing an auto-encoder architecture, the system designs and optimizes constellation mappings to b...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on vehicular technology Jg. 74; H. 8; S. 13219 - 13224
Hauptverfasser:	Hu, Jiaming, Han, Kawon, Jiang, Lai, Meng, Kaitao, Liu, Fan, Masouros, Christos
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.08.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Deep learning Integrated sensing and communication Integrated sensing and communications (ISAC) Measurement multiple imput and multiple output (MIMO) OFDM Orthogonal Frequency Division Multiplexing orthogonal frequency division multiplexing (OFDM) precoder design Radar Receivers Symbols Time-domain analysis Training Uplink Uplinking Vectors
ISSN:	0018-9545, 1939-9359
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!