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Stream/Area:
-
Subject:
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Paper ID:
IJSREM62364
Volume:
10 |
5 |
May 2026
Pages:
1-9
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Electronics and Communication Engineering
SDBCT, Indore
Electronics and Communication Engineering
SDBCT, Indore
Electronics and Communication Engineering
SDBCT, Indore
Due to increasing number of users and multimedia applications, multiple input, multiple output (MIMO) systems have become indispensable from wireless technology. The benefit of MIMO systems is increase in the channel capacity at low bandwidths, however, the accurate reception of the MIMO signal at the receiver is extremely complex. This is due to the addition of noise and interference, as well as the different behavior of the wireless channel for the different channel paths. Due to the largeness and the complexity of the data, the technique used off late is the Deep Learning based approach for signal detection. This paper presents the basics of MIMO systems and insight into deep learning based MIMO channel estimation and signal detection techniques.
KEYWORDS
It can be concluded that MIMO systems and moreover massive MIMO systems are the only way out to provide limited bandwidth yet bandwidth hungry applications. Massive MIMO may serve as a technique to increase the system capacity and date rate. However, MIMO systems suffer from distortion effects. This is due to the addition of noise and interference, as well as the different behavior of the wireless channel for the different channel paths. Due to the largeness and the complexity of the data, the technique used off late is the Deep Learning based approach for signal detection. This paper presents a comprehensive review of machine learning and deep learning assisted massive MIMO systems along with the salient features of the approaches. It is expected that the paper will serve as an effective tool to find future directions of research.
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Publication Date
5/5/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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