A Hybrid Deep Learning Framework for OFDM with Index Modulation Under Uncertain Channel Conditions

Index modulation (IM) is considered a promising approach for fifth-generation wireless systems due to its spectral efficiency and reduced complexity compared to conventional modulation techniques. However, IM faces difficulties in environments with unpredictable channel conditions, particularly in a...

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Bibliographic Details
Main Authors:	Md Abdul Aziz, Md Habibur Rahman, Rana Tabassum, Mohammad Abrar Shakil Sejan, Myung-Sun Baek, Hyoung-Kyu Song
Format:	Article
Language:	English
Published:	MDPI AG 2024-11-01
Series:	Mathematics
Subjects:	orthogonal frequency-division multiplexing (OFDM) wireless communication index modulation (IM) deep learning (DL) imperfect channel conditions bidirectional long short-term memory (Bi-LSTM)
Online Access:	https://www.mdpi.com/2227-7390/12/22/3583
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A Hybrid Deep Learning Framework for OFDM with Index Modulation Under Uncertain Channel Conditions

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