NDLI: A new Shifted Scaled LS channel estimator for Rician flat fading MIMO channel

Content Provider	IEEE Xplore Digital Library
Author	Nooralizadeh, H. Moghaddam, S.S.
Copyright Year	2009
Description	Author affiliation: Electrical Engineering Dept., Science and Research Branch, Islamic Azad University, Tehran, Iran (Nooralizadeh, H.) \|\| Electrical Engineering Dept., Shahid Rajaee, Teacher Training University, Tehran, Iran (Moghaddam, S.S.)
Abstract	In this paper, Training-Based Channel Estimation (TBCE) method is considered in the Rician flat fading Multiple-Input Multiple-Output (MIMO) channels. In this channel model, the performance of the conventional Least Squares (LS) channel estimator is probed first. A new shifted type of Scaled Least Squares (SLS) channel estimator, entitled as SSLS, is then proposed. It is a generalized form of the SLS technique. The optimal choice of training signals using Mean Square Error (MSE) criterion is also achieved. It is observed that the LS estimator cannot exploit the knowledge of channel statistics. However, the SSLS estimator exploits the trace of a specifically defined matrix of the channel covariance and the receiver noise power as well as the knowledge of first-order statistics about the channel. It is shown that in the Rician fading MIMO channel, the new channel estimator has better performance than the popular LS and SLS techniques. Theoretical analysis and simulation results demonstrate that increasing Rice factor is a reason for decreasing MSE of the proposed estimator.
Starting Page	243
Ending Page	247
File Size	403128
Page Count	5
File Format	PDF
ISBN	9781424446810
DOI	10.1109/ISIEA.2009.5356473
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-04
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fading Training Based Channel Estimation Laser sintering Covariance matrix Least squares approximation Statistics Analytical models Rician channels Channel estimation Mean square error methods Multiple-Input Multiple-Output (MIMO) MIMO Rician Fading Shifted Scaled Least Squares (SSLS)
Content Type	Text
Resource Type	Article

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