A Markovian Model-Driven Deep Learning Framework for Massive MIMO CSI Feedback

Channel state information (CSI) plays a vital role in scheduling and capacity-approaching transmission optimization of massive MIMO communication systems. In frequency division duplex (FDD) MIMO systems, forward link CSI reconstruction at transmitter relies on CSI feedback from receiving nodes and m...

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Veröffentlicht in:	IEEE transactions on wireless communications 2022-02, Vol.21 (2), p.1214-1228
Hauptverfasser:	Liu, Zhenyu, del Rosario, Mason, Ding, Zhi
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Bandwidth channel estimation Coherence Communications systems compression Computing costs Deep learning Downlink Fading channels Feedback Frequency division duplexing MarkovNet Massive MIMO MIMO communication model-driven learning Neural networks Optimization Reconstruction Recurrent neural networks Wireless communication
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