| Summary: | 碩士 === 逢甲大學 === 通訊工程學系 === 102 === Abstract
In wireless communications, the propagation of radio signals through channels is usually affected by channel fading, intersymbol interference, multiple paths and noise. Hence we need to design equalizers at the receiver to account for these effects and to recover the source signals. However, to realize the equalization, we need to obtain the channel state information.
This thesis proposes three blind estimation methods for multiple-input multiple-output channels based on (3,1) repetition code. They are traditional subspace method, repetition index-based subspace method, and eigendecomposition-based method. The first two algorithms compute the channel impulse response matrix by exploiting the orthogonality of the signal and noise subspaces of the autocorrelation matrix of the received data; while the last algorithm first compute the channel product matrices from the received data and then determine the channel impulse response matrix via an eigendecomposition.
In addition, thanks to (3,1) repetition code, the equalization process can be carried out in frequency domain, which reduces the processing complexity of signal recovery at the receiver. Simulation results are used to demonstrate the performance of the proposed methods.
Key words: multiple-input multiple-output、repetition index、subspace、eigendecomposition、repetition codes、blind estimation
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