Performance Enhancement of MmWave MIMO Systems Using Deep Learning Framework

In order to obtain beamforming gains and prevent high pathloss in millimeter wave (mmWave) systems, large number of antennas is employed. Digital precoders are difficult to implement with many antennas because of hardware constraints, while analog precoders have limited performance. In this paper, h...

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Vydané v:	IEEE access Ročník 9; s. 1
Hlavní autori:	Faragallah, Osama S., El-sayed, Hala S., El-Mashed, Mohamed G.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Antennas Array signal processing Beamforming Covariance matrix Decoder Decoders Deep learning Digital precoders Hardware HybridPrecodingNet Millimeter waves mmWave MmWave and Spectral Efficiency Neural networks Optimization Performance enhancement Precoding Radio frequency Spectral efficiency
ISSN:	2169-3536, 2169-3536
On-line prístup:	Získať plný text
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