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Semi-blind Channel Estimation and Decoding for Space-Time Block coded System

The paper addresses the problem of semi-blind channel estimation and decoding for space-time coded system over time-varying fading channel. We derive a state-space model that characterizes the space-time coded system. The channel estimation is performed using a kalman filtering method which operates in two modes: training mode and blind mode. Box-constrained ML algorithm is used to perform the decoding function under the previous state-space system model. The performance of channel estimation and decoding schemes are investigated by computer simulations