Fast Semi-Blind Channel Estimation for MIMO-OFDM Systems with Virtual Carriers

碩士 === 輔仁大學 === 電機工程學系 === 101 === In an orthogonal frequency-division multiplexing (OFDM) system with multiple-input and multiple-out channels, intersymbol interference(ISI) is caused by a multipath fading channel. Zero Padding (ZP) or cyclic prefix (CP) must be added to cope with this problem. Thi...

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Bibliographic Details
Main Authors: Wan-Ru Kuo, 郭婉如
Other Authors: Jung-Lang Yu
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/56875096080447278554
Description
Summary:碩士 === 輔仁大學 === 電機工程學系 === 101 === In an orthogonal frequency-division multiplexing (OFDM) system with multiple-input and multiple-out channels, intersymbol interference(ISI) is caused by a multipath fading channel. Zero Padding (ZP) or cyclic prefix (CP) must be added to cope with this problem. This research was designed to investigate the porformance of channel estimation when the virtual carrier (VC) is added in CP-OFDM system. In terms of methods used for channel estimation, subspace (ss)-based blind channel estimation methods have been widely applied. However, the restriction of this method is a large amount of OFDM symbols are required for channel estimation. In contrast, the block matrix scheme we used in this study that produces a great amount of data can still be used for channel estimation even if the receiver does not receive many OFDM symbols. In this study, we investigated three methods for channel estimation and simulated three methods with different channels to compare performance. The first two methods in this study were traditional subspace (ss)-based blind channel estimation, and subspace (ss)-based blind channel estimation methods that are assisted by a block matrix scheme(BMS). For the last method, we integrated subspace (ss)-based blind channel estimation and improved semi-blind channel estimation methods. Finally, we utilized minimum mean-square-error equalizer and Zero Forcing equalizer to detect symbols. The simulation results indicated our improved semi-blind channel estimation method is better at decreasing bit error rate and enhancing convergence rates than the block matrix scheme method and Shin’s method.