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Review of Deep Neural Network Detectors in SM MIMO System

Authors :
Ruksana. P
Radhika. P
Publication Year :
2020
Publisher :
Zenodo, 2020.

Abstract

A deep neural network detector for SM MIMO has been proposed. Its detection principle is deep learning. For this a neural network must be trained first, and then used for detection purpose. It doesn’t need any channel model and instantaneous channel state information CSI . It can provide better bit error performance compared with conventional viterbi detector VD and also it can detect any length of sequences. For a MIMO system, the channel estimation complexity can be avoided. It can detect in real time as arrives the receiver. The main benefit is it can be used where the channel model is difficult to design and also the channel is continuously varying with time. Ruksana. P | Radhika. P "Review of Deep Neural Network Detectors in SM-MIMO System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30535.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/30535/review-of-deep-neural-network-detectors-in-smmimo-system/ruksana-p

Details

Language :
English
ISSN :
24566470
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....1ebdad088629a4519babff00faed47d0
Full Text :
https://doi.org/10.5281/zenodo.3892371