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)...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on communications Ročník 69; číslo 1; s. 529 - 543
Hlavní autoři:	Srivastava, Suraj, Singh, Prem, Jagannatham, Aditya K., Karandikar, Abhay, Hanzo, Lajos
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!