CNN-Based Precoder and Combiner Design in mmWave MIMO Systems
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Dosyalar
Tarih
2019
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee-Inst Electrical Electronics Engineers Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Hybrid beamformer design is a crucial stage in millimeter-wave (mmWave) MIMO systems. In this letter, we propose a convolutional neural network (CNN) framework for the joint design of precoder and combiners. The proposed network accepts the input of channel matrix and gives the output of analog and baseband beamformers. Previous works are usually based on the knowledge of steering vectors of array responses which is not always accurately available in practice. The proposed CNN framework does not require such a knowledge, and it provides higher performance in capacity compared with the conventional greedy-and optimization-based algorithms.
Açıklama
Elbir, Ahmet M./0000-0003-4060-3781
WOS: 000475331600032
WOS: 000475331600032
Anahtar Kelimeler
mmWave, MIMO, hybrid beamforming, deep learning, convolutional neural network
Kaynak
Ieee Communications Letters
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
23
Sayı
7
