On Investigations of Machine Learning and Deep Learning Techniques for MIMO Detection

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Published: Aug 18, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i8s.7220
Keywords:
ML, DL, AI, MIMO detection, mMIMO

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Mehak Saini
Ph.D. research scholar, Deptt. of ECE, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Haryana, India
Surender K. Grewal
Deptt. of ECE, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Haryana, India

Abstract

This paper reviews in detail the various types of multiple input multiple output (MIMO) detector algorithms. The current MIMO detectors are not suitable for massive MIMO (mMIMO) scenarios where there are a large number of antennas. Their performance degrades with the increase in number of antennas in the MIMO system. For combatting the issues, machine learning (ML) and deep learning (DL) based detection algorithms are being researched and developed. An extensive survey of these detectors is provided in this paper, alongwith their advantages and challenges. The issues discussed have to be resolved before using them for final deployment.

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How to Cite
Saini, M. ., & Grewal, S. K. . (2023). On Investigations of Machine Learning and Deep Learning Techniques for MIMO Detection . International Journal on Recent and Innovation Trends in Computing and Communication, 11(8s), 406–414. https://doi.org/10.17762/ijritcc.v11i8s.7220
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Vol. 11 No. 8s (2023)
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Articles

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