| Summary: | 博士 === 國立清華大學 === 電機工程學系 === 96 === In this study, we propose a novel full-diversity combination algorithm for blind channel estimation and equalization, which takes advantage of the full-diversity gain of the multipath fading channel and executes a smoother filter operation to significantly improve the performance of the network Kalman-based blind equalizers. The proposed full-diversity blind equalizer based on the weighted Gaussian sum (WGS) technique and the network of extended Kalman filters, employs the prediction errors of network of Kalman filters to achieve the maximum likelihood (ML) solution. Therefore, the proposed algorithm can effectively estimate both the channel coefficients and the transmitted symbols over the fast time-varying inter-symbol interference (ISI) fading channels. The fast time-varying ISI fading channel is modeled by a second order autoregressive (AR(2)) process according to the Doppler frequency shift in cellular networks. Simulation results illustrate that the proposed blind equalizer based on the full-diversity combination algorithm can track the fast time-varying fading channel much more accurately than the conventional network Kalman-based blind equalizers. For symbol detection, the proposed diversity combination blind equalizers demonstrate a significant improvement compared with the conventional WGS-IMM (Interacting Multiple Model) blind equalizers in the bit error rate (BER) performance.
Besides, from the trade-off consideration between the performance and the computational complexity, the proposed modified 2-Diversity blind equalizer is a best choice for the WGS-based blind equalizer. Because the proposed 2-Diversity blind equalizer avoids the exponential growth of the computational complexity making it feasible for wireless communication systems.
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