Bayesian Learning-Based Doubly-Selective Sparse Channel Estimation for Millimeter Wave Hybrid MIMO-FBMC-OQAM Systems

We design and analyse filter bank multicarrier (FBMC) offset quadrature amplitude modulation (OQAM)-based millimeter wave (mmWave) hybrid multiple-input multiple-output (MIMO) systems. Furthermore, a novel channel estimation model is conceived for quasi-static mmWave hybrid MIMO-FBMC-OQAM (mmH-MFO)...

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Vydané v:	IEEE transactions on communications Ročník 69; číslo 1; s. 529 - 543
Hlavní autori:	Srivastava, Suraj, Singh, Prem, Jagannatham, Aditya K., Karandikar, Abhay, Hanzo, Lajos
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Baseband Bayes methods Bayesian analysis Bayesian Cramér-Rao bound Bayesian learning (BL) Channel estimation Circuits Design analysis expectation maximization filter bank multicarrier Filter banks hybrid MIMO architecture Hybrid systems Kalman filters Lower bounds Machine learning Millimeter waves MIMO (control systems) MIMO communication mmWave communication OFDM Quadrature amplitude modulation Radio frequency Subcarriers
ISSN:	0090-6778, 1558-0857
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