Performance evaluation of DFT-based channel estimation in MIMO-OFDM system
by R.S. Ganesh; J. Jayakumari
International Journal of Enterprise Network Management (IJENM), Vol. 7, No. 2, 2016

Abstract: Multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) is an emerging multiplexing technique used in modern mobile communication systems. A main challenge to MIMO-OFDM is retrieval of the channel state information (CSI) accurately and synchronisation between the transmitter and receiver. The CSI is retrieved with the help of channel estimation algorithms such as training-based, blind and semi-blind channel estimation by various researchers. The mean square error (MSE) of existing training-based least square (LS) and minimum mean square error (MMSE) estimation are usually high. In order to minimise MSE, discrete Fourier transform (DFT)-based channel estimation is proposed. This paper deals with MIMO-OFDM system and simulation of training-based LS and MMSE channel estimation, performance evaluation of DFT-based channel estimation. The simulation results clearly indicate the drastic minimisation of MSE by the implementation of DFT channel estimation with LS and MMSE estimation.

Online publication date: Tue, 05-Jul-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Enterprise Network Management (IJENM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com