English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Accurate channel estimation is critical to the performance of orthogonalfrequency-division multiplexing (OFDM) underwater acoustic (UWA)communications, especially under multiple-input multiple-output (MIMO)scenarios. In this paper, we explore Vector Approximate Message Passing (VAMP)coupled with Expected Maximum (EM) to obtain channel estimation (CE) for MIMOOFDM UWA communications. The EM-VAMP-CE scheme is developed by employing aBernoulli-Gaussian (BG) prior distribution for the channel impulse response,and hyperparameters of the BG prior distribution are learned via the EMalgorithm. Performance of the EM-VAMP-CE is evaluated through both synthesizeddata and real data collected in two at-sea UWA communication experiments. It isshown the EM-VAMP-CE achieves better performance-complexity tradeoff comparedwith existing channel estimation methods.

Vector Approximate Message Passing based Channel Estimation for MIMO-OFDM Underwater Acoustic Communications