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Please use this identifier to cite or link to this item: http://hdl.handle.net/10012/4459

Title: Simplified Channel Estimation Techniques for OFDM Systems with Realistic Indoor Fading Channels
Authors: Hwang, Jake
Keywords: OFDM
Channel Estimation
Approved Date: 22-May-2009
Date Submitted: 5-May-2009
Abstract: This dissertation deals with the channel estimation techniques for orthogonal frequency division multiplexing (OFDM) systems such as in IEEE 802.11. Although there has been a great amount of research in this area, characterization of typical wireless indoor environments and design of channel estimation schemes that are both robust and practical for such channel conditions have not been thoroughly investigated. It is well known that the minimum mean-square-error (MMSE) estimator provides the best mean-square-error (MSE) performance given a priori knowledge of channel statistics and operating signal-to-noise ratio (SNR). However, the channel statistics are usually unknown and the MMSE estimator has too much computational complexity to be realized in practical systems. In this work, we propose two simple channel estimation techniques: one that is based on modifying the channel correlation matrix from the MMSE estimator and the other one with averaging window based on the LS estimates. We also study the characteristics of several realistic indoor channel models that are of potential use for wireless local area networks (LANs). The first method, namely MMSE-exponential-Rhh, does not depend heavily on the channel statistics and yet offer performance improvement compared to that of the LS estimator. The simulation results also show that the second method, namely averaging window (AW) estimator, provides the best performance at moderate SNR range.
Program: Electrical and Computer Engineering
Department: Electrical and Computer Engineering
Degree: Master of Applied Science
URI: http://hdl.handle.net/10012/4459
Appears in Collections:Faculty of Engineering Theses and Dissertations
Electronic Theses and Dissertations (UW)

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