Optimum Averaging of Superimposed Training Schemes in OFDM Under Realistic Time-Variant Channels

Optimum Averaging of Superimposed Training Schemes in OFDM Under Realistic Time-Variant Channels

The current global bandwidth shortage in orthogonal frequency division multiplexing (OFDM)-based systems motivates the use of more spectrally efficient techniques. Superimposed training (ST) is a candidate in this regard because it exhibits no information rate loss. Additionally, it is very flexible...

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Bibliographic Details
Main Authors: Ignasi Pique Muntane, M. Julia Fernandez-Getino Garcia
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
OFDM
superimposed training
time-variant channel
channel estimation
least squares
optimization
Online Access:https://ieeexplore.ieee.org/document/9514564/

Internet

https://ieeexplore.ieee.org/document/9514564/

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