GA Based Estimation of Sparse MIMO Channels with Superimposed Training

GA Based Estimation of Sparse MIMO Channels with Superimposed Training

Multiple-input multiple-output (MIMO) techniques are foreseen to play a vital role in future 5G cellular networks. This paper presents a novel approach that employs genetic algorithm (GA) to estimate the sparse uplink MIMO channels using superimposed training sequence (SiT). At each transmitter (use...

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Bibliographic Details
Main Authors: Babar Mansoor, Syed Junaid Nawaz, Moazzam Islam Tiwana, Junaid Ahmed, Abdul Haseeb
Format: Article
Language:English
Published: Kaunas University of Technology 2018-12-01
Series:Elektronika ir Elektrotechnika
Subjects:
channel estimation
equalization
mimo
genetic algorithms
superimposed training.
Online Access:http://eejournal.ktu.lt/index.php/elt/article/view/22294

Internet

http://eejournal.ktu.lt/index.php/elt/article/view/22294

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