HyDNN: A Hybrid Deep Learning Framework Based Multiuser Uplink Channel Estimation and Signal Detection for NOMA-OFDM System

HyDNN: A Hybrid Deep Learning Framework Based Multiuser Uplink Channel Estimation and Signal Detection for NOMA-OFDM System

Deep learning (DL) techniques can significantly improve successive interference cancellation (SIC) performance for the non-orthogonal multiple access (NOMA) system. The NOMA-orthogonal frequency division multiplexing (OFDM) system is considered in this paper to develop a hybrid deep neural network (...

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Bibliographic Details
Main Authors: Md Habibur Rahman, Mohammad Abrar Shakil Sejan, Md Abdul Aziz, Young-Hwan You, Hyoung-Kyu Song
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
1D-CNN
BiLSTM
symbol error performance
uplink NOMA
OFDM
multiuser signal detection (SD)
Online Access:https://ieeexplore.ieee.org/document/10167605/

Internet

https://ieeexplore.ieee.org/document/10167605/

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