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A Spatio-temporal Residual Attention Network with SNR-adaptive Weighting for MIMO-OFDM Channel Estimation, Journal of Telecommunications and Information Technology, 2026, nr 3
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Tytuł: A Spatio-temporal Residual Attention Network with SNR-adaptive Weighting for MIMO-OFDM Channel Estimation, Journal of Telecommunications and Information Technology, 2026, nr 3

Autor:

El-azizi, Ousama ; Fateh, Rachid ; Said, Safi

Data wydania:

2026, nr 3

Typ zasobu:

artykuł

Tytuł publikacji grupowej:

2026, nr 3, JTIT-artykuły

Opis:

kwartalnik

Abstrakt:

This paper addresses channel estimation in MIMO-OFDM systems under time-varying Rician fading and spatially correlated propagation conditions, where reliable coherent detection requires accurate channel state information. Although least-squares (LS) estimation is simple and computationally efficient, it remains highly sensitive to noise. In addition, conventional deep learning-based estimators may suffer from tracking bias when temporal channel variations are not properly handled. To overcome these imitations, this paper proposes SMART-CE, a spatio-temporal residual attention network with SNR-adaptive weighting. The proposed approach refines a sequence of LS estimates by extracting spatial-frequency features, exploiting temporal channel correlation, and adaptively balancing historical and current channel information according to the operating SNR. The final channel estimate is obtained through a residual correction of the current LS estimate. Simulation results on an 8 x 8 MIMO-OFDM system show that SMART-CE generally achieves lower NMSE and BER than CNN, residual CNN, residual-attention CNN, recursive least-squares (RLS), and normalized least-mean-square (NLMS) baselines, with the most pronounced gains observed in the low-to-medium SNR regime.

Tom:

105

Numer:

3

Wydawca:

National Institute of Telecommunications

Identyfikator zasobu:

oai:bc.itl.waw.pl:2477

DOI:

10.26636/jtit.2026.3.2688

eISSN:

1899-8852

Źródło:

Journal of Telecommunications and Information Technology

Język:

ang

Prawa:

Biblioteka Naukowa Instytutu Łączności

Licencja:

CC BY 4.0

Właściciel praw:

Biblioteka Naukowa Instytutu Łączności

Temat i słowa kluczowe:

channel estimation deep learning MIMO-OFDM NLMS NMSE residual attention Rician fading RLS SNR-adaptive weighting

Kolekcje, do których przypisany jest obiekt:

Data ostatniej modyfikacji:

2 paź 2026

Data dodania obiektu:

2 paź 2026

Liczba wyświetleń treści obiektu:

1

Wszystkie dostępne wersje tego obiektu:

https://bc.itl.waw.pl/publication/2800

Wyświetl opis w formacie RDF:

RDF

Wyświetl opis w formacie OAI-PMH:

OAI-PMH

Nazwa wydania Data
El-azizi, Ousama; Fateh, Rachid; Said, Safi, A Spatio-temporal Residual Attention Network with SNR-adaptive Weighting for MIMO-OFDM Channel Estimation, Journal of Telecommunications and Information Technology, 2026, nr 3 2 paź 2026

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