Review of Deep Neural Network Detectors in SM-MIMO System

Radhika. P; Ruksana. P

Title:
Review of Deep Neural Network Detectors in SM-MIMO System

Authors:
Ruksana. P | Radhika. P

Cite This Article :

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, pp.534-535, URL: https://www.ijtsrd.com/papers/ijtsrd30535.pdf

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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.

Keywords :
Spatial Modulation, Deep Learning, Neural Network, Channel State Information, Viterbi Detector

Publication Details:

Unique Identification Number : IJTSRD30535

Published In : Volume-4 | Issue-3, April 2020

Page Number(s) : 534-535

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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