Sparse Bayesian Learning for Channel Estimation in Time-Varying Underwater Acoustic OFDM Communication

Sparse Bayesian Learning for Channel Estimation in Time-Varying Underwater Acoustic OFDM Communication

In this paper, we study the sparse Bayesian learning (SBL) framework for channel estimation in underwater acoustic (UWA) orthogonal frequency-division multiplexing (OFDM) communication systems, which provides a desirable property of preventing structural error with fewer convergence errors for spars...

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Bibliographic Details
Main Authors: Gang Qiao, Qingjun Song, Lu Ma, Songzuo Liu, Zongxin Sun, Shuwei Gan
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Time-varying UWA channels
sparse channel estimation
sparse Bayesian learning
orthogonal frequency division multiplexing
Online Access:https://ieeexplore.ieee.org/document/8478304/

Internet

https://ieeexplore.ieee.org/document/8478304/

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