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

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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