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Blind Channel Estimation and Equalization Based on ICA in MIMO-OFDM System
Author: JiangCheng
Tutor: ZhaoXiaoZuo
School: Jilin University
Course: Signal and Information Processing
Keywords: Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing Subspace blind channel estimation Space-time equalizer Independent variable analysis
CLC: TN919.3
Type: Master's thesis
Year: 2009
Downloads: 182
Quote: 2
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Abstract
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MIMO (Multiple-Input Multiple-Output, MIMO) system in the case of need to increase the spectrum resource and the antenna transmission power can be doubled to improve the channel capacity . Orthogonal Frequency Division Multiplexing (Orthogonal Frequency Division Multiplexing, OFDM) technique can be effective against the frequency selective multipath fading . The combination of the MIMO-OFDM system will be very promising high data rate transmission scheme . Wireless propagation environment , both sub-channel interference ICI and multi - access interference MAI, need to be balanced and balanced space . The MIMO-OFDM system , blind channel estimation and equalization purposes is not using the training sequence , the estimated channel information , and to eliminate the ICI and the MAI in the signal transmission process , to restore the user data . In this paper, based on second-order statistics subspace blind channel estimation algorithm , the same column space and the use of the received signal vector channel transmission matrix column space of this nature , by calculating the received signal vector self- Related obtain the noise subspace , then construct channel parameter as a variable equation of secondary consideration to minimize this cost equation with space fuzzy factor channel parameters . The MMSE equalizer then based on the results of the estimated completion time equalizer , and put forward an improved low-dimensional equalization scheme . Balanced results based on the time remaining space law ICA eliminates time equalizer fuzzy factor , complete spatial equilibrium , restore user data analysis based on higher-order statistics of independent variables , statistically independent source and non - Gaussian conditions . Simulation results show that ICA assisted MMSE equalizer shows a good performance .
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