Learning-Aided Beam Prediction in mmWave MU-MIMO Systems for High-Speed Railway

The problem of beam alignment and tracking in high mobility scenarios such as high-speed railway(HSR) becomes extremely challenging, since large overhead cost and significant time delay are introduced for fast time-varying channel estimation. To tackle this challenge, we propose a learning-aided bea...

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Vydáno v:	IEEE transactions on communications Ročník 70; číslo 1; s. 693 - 706
Hlavní autoři:	Meng, Fan, Liu, Shengheng, Huang, Yongming, Lu, Zhaohua
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.01.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	alternating optimization Amplitudes Array signal processing Beam prediction Beamforming data fusion Data integration High speed rail high-speed railway hybrid precoder Learning Maximum likelihood estimates Maximum likelihood estimation Millimeter waves Modules Overhead costs Parameter estimation Predictive models Radio frequency Railway tracks Time lag Training
ISSN:	0090-6778, 1558-0857
On-line přístup:	Získat plný text
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