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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Autori principali:	Gang Qiao, Qingjun Song, Lu Ma, Songzuo Liu, Zongxin Sun, Shuwei Gan
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	IEEE 2018-01-01
Serie:	IEEE Access
Soggetti:	Time-varying UWA channels sparse channel estimation sparse Bayesian learning orthogonal frequency division multiplexing
Accesso online:	https://ieeexplore.ieee.org/document/8478304/
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