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Table 1 Summary of existing surveys, magazines, and review papers related to artificial intelligence for channel estimation in multicarrier systems

From: Artificial intelligence for channel estimation in multicarrier systems for B5G/6G communications: a survey

Ref.

Summary and focus

Muticarrier systems

Dedicated to AI-based channel estimation?

AI-based channel estimation discussion

Brief

Moderate

Extensive

[21]

A discussion about the motivations for employing AI-enabled cellular networks.

OFDM

No

\(\checkmark\)

  

[22]

A discussion about key requirements, challenges, deployment strategies, and enabling technologies for applying deep learning in 6G future communication systems physical layer.

OFDM

No

\(\checkmark\)

  

[23]

A summary of deep learning-based physical layer application in 5G wireless communication systems.

OFDM

No

\(\checkmark\)

  

[24]

A comparison of deep learning-based channel estimation with conventional methods.

OFDM

Yes

 

\(\checkmark\)

 

[39]

An overview of deep learning usage in a wireless networks, comprising different layers.

OFDM

No

\(\checkmark\)

  

[40]

A survey on massive MIMO channel techniques for modeling and estimation.

OFDM

No

\(\checkmark\)

  

[41]

An extensive survey on deep learning in mobile and wireless networks.

OFDM

No

\(\checkmark\)

  

[32]

A machine learning techniques overview to solve different challenges in wireless networks.

OFDM

No

\(\checkmark\)

  

[33]

A review of applications of machine learning techniques for the next-generation wireless network.

OFDM

No

\(\checkmark\)

  

[30]

A discussion about mMIMO channel estimation techniques using deep learning.

OFDM

No

\(\checkmark\)

  

[42]

A discussion about deep learning in terms of model-based block architecture and algorithm design for wireless communication.

OFDM

No

\(\checkmark\)

  

[43]

A comprehensive survey on machine learning applications in the vehicular network context.

OFDM

No

 

\(\checkmark\)

 

[44]

A survey of four intelligent signal processing topics for the wireless physical layer of MIMO systems: modulation classification, signal detection, beamforming, and channel estimation.

OFDM

No

 

\(\checkmark\)

 

[45]

A discussion about several novel deep learning applications for the physical layer.

–

No

\(\checkmark\)

  

[46]

A physical layer review of the challenges of machine learning in wireless communication.

OFDM

No

\(\checkmark\)

  

[47]

Performance analysis of machine learning applied to channel estimation.

OFDM

Yes

 

\(\checkmark\)

 

[48]

A tutorial on recurrent neural networks for channel prediction.

OFDM

Yes

 

\(\checkmark\)

 

[49]

A brief review of deep learning channel estimation techniques for wireless systems.

OFDM

Yes

 

\(\checkmark\)

 

[50]

A comprehensive overview of model-driven deep learning in physical layer communications.

OFDM

No

\(\checkmark\)

  

[31]

A discussion about deep learning-based block-structured functions for the physical layer and deep learning-based end-to-end communication systems.

OFDM

No

\(\checkmark\)

  

[51]

An overview of deep learning wireless communication systems applied to the physical layer.

OFDM

No

\(\checkmark\)

  

This work

A comprehensive survey of AI-based channel estimation techniques for multicarrier systems comprising classical machine learning techniques and neural networks.

OFDM, GFDM, FBMC, UMFC

Yes

  

\(\checkmark\)