Abstract
In order to estimate a fading channel characteristics, a pilot signal is propogated with traffic channel. Fading channel parameter estimation is of paramount importance as it may be utilized to design different equalization techniques. It may also be utilized to allocate weights of rake receiver to sturdiest multipaths as well as coherent reception and weighted combination of multipath constituents of wireless communication systems. In this paper, a pilot aided channel estimating technique for MIMO-CDMA systems is presented. This technique utilizes minimum mean squared error estimation of corrupted information in a flat fading channel along with noise. Simulation results predicts theoretical predictions are strongly validated for different values of SNR and users.
Highlights
A Novel Design of Pilot Aided Channel Estimation for MIMO-code division multiple access (CDMA) SystemAbstract—In order to estimate a fading channel characteristics, a pilot signal is propogated with traffic channel
Design of an efficient receiver in code division multiple access (CDMA) system is perplexing as output information carrying signal is compromised by Gaussian noise corrupted, interference and random nature of a flat fading channel
Fading channel parameter estimation is of paramount importance as it may be utilized to design linear and decision feedback equalizers
Summary
Abstract—In order to estimate a fading channel characteristics, a pilot signal is propogated with traffic channel. Fading channel parameter estimation is of paramount importance as it may be utilized to design different equalization techniques. It may be utilized to allocate weights of rake receiver to sturdiest multipaths as well as coherent reception and weighted combination of multipath constituents of wireless communication systems. A pilot aided channel estimating technique for MIMO-CDMA systems is presented. This technique utilizes minimum mean squared error estimation of corrupted information in a flat fading channel along with noise. Simulation results predicts theoretical predictions are strongly validated for different values of SNR and users
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