Learning Linear Filters for Underwater OFDM Channel Estimation with Attention-Aided MMSE

한국통신학회논문지 2026

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Authors: T.T. Ha, Jeonghun Park
DOI: 10.7840/kics.2026.51.1.121
Cited by: 0

Abstract

This letter presents an Attention-aided MMSE (AMMSE) channel estimation method for underwater OFDM systems. To address the severe time variation and multipath effects in underwater acoustic channels, AMMSE leverages a Transformer to learn a linear MMSE filter from data, capturing temporal and spectral correlations. Inference involves only a matrix-vector multiplication, ensuring low complexity. Simulations show that AMMSE outperforms LS, 1D-MMSE, and MMSE across all SNRs, with significant gains in low-SNR conditions.

Fields of Study & Subjects

Underwater Vehicles and Communication Systems Advanced Wireless Communication Techniques PAPR reduction in OFDM

Publication details

Journal / source
한국통신학회논문지
Volume
51
Issue
1
Pages
121–124
Publication date
29 January 2026
Language
EN