Machine learning-based 5G-and-beyond channel estimation for MIMO-OFDM communication systems
Channel estimation plays a critical role in the system performance of wireless networks. In
addition, deep learning has demonstrated significant improvements in enhancing the …
addition, deep learning has demonstrated significant improvements in enhancing the …
LSTM-based distributed conditional generative adversarial network for data-driven 5G-enabled maritime UAV communications
5G enabled maritime unmanned aerial vehicle (UAV) communication is one of the important
applications of 5G wireless network which requires minimum latency and higher reliability to …
applications of 5G wireless network which requires minimum latency and higher reliability to …
Channel state information estimation for 5G wireless communication systems: recurrent neural networks approach
In this study, a deep learning bidirectional long short-term memory (BiLSTM) recurrent
neural network-based channel state information estimator is proposed for 5G orthogonal …
neural network-based channel state information estimator is proposed for 5G orthogonal …
A review of wireless channel estimation techniques: challenges and solutions
MN Drakshayini, MR Kounte - International Journal of …, 2022 - inderscienceonline.com
In wireless communication, the transmitted signal is subjected to distortion, noise, frequency
shift, non-linear attenuation, fading, and so on due to the inherent nature of the physical …
shift, non-linear attenuation, fading, and so on due to the inherent nature of the physical …
Multi-user joint detection using bi-directional deep neural network framework in NOMA-OFDM system
Non-orthogonal multiple access (NOMA) has great potential to implement the fifth-
generation (5G) requirements of wireless communication. For a NOMA traditional detection …
generation (5G) requirements of wireless communication. For a NOMA traditional detection …
A survey of fdd-based channel estimation schemes with coordinated multipoint
New enabling technologies that include millimeter wave (mmWave) communication,
massive multiple-input-multiple-output (MIMO), and ultradense networks are set to transform …
massive multiple-input-multiple-output (MIMO), and ultradense networks are set to transform …
Multiuser adversarial attack on deep learning for OFDM detection
Adversarial attack has been widely used to degrade the performance of deep learning (DL),
especially in the field of communications. In this letter, we evaluate different white-box and …
especially in the field of communications. In this letter, we evaluate different white-box and …
Channel estimation and symbol demodulation for OFDM systems over rapidly varying multipath channels with hybrid deep neural networks
We consider orthogonal frequency division multiplexing over rapidly time-varying multipath
channels, for which performance of standard channel estimation and equalization …
channels, for which performance of standard channel estimation and equalization …
Bi‐directional LSTM based channel estimation in 5G massive MIMO OFDM systems over TDL‐C model with Rayleigh fading distribution
R Shankar - International Journal of Communication Systems, 2023 - Wiley Online Library
In this work, a deep learning (DL)‐based massive multiple‐input multiple‐output (mMIMO)
orthogonal frequency division multiplexing (OFDM) system is investigated over the tapped …
orthogonal frequency division multiplexing (OFDM) system is investigated over the tapped …
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 …
cancellation (SIC) performance for the non-orthogonal multiple access (NOMA) system. The …