Soft-Decision-Aided Channel Estimation Over the Flat-Fading Channel, and an Application to Iterative Decoding Using an Example LTE Turbo Code

We consider transmissions over the frequency-nonselective time-selective fading channel and derive the soft-decision-aided maximum a posteriori probability (SDA-MAP) channel estimator that utilizes the entire received signal sequence, including both pilot signals and data signals, and the a priori statistical information of the transmitted data symbols. This paper theoretically demonstrates how the soft data decisions should be incorporated into the channel estimation process. An iterative implementation of the SDA-MAP estimator is proposed, which uses the feedback of earlier soft decisions and the feedforward of later soft decisions to estimate the current channel gain. This approximate SDA-MAP implementation is similar in structure to the expectation-maximization algorithm. Simulation results show that the receiver using this iterative SDA-MAP estimator outperforms the conventional pilot-symbol-assisted modulation receiver in which the channel estimates are obtained from only the pilot signals. An application to iterative decoding using the LTE turbo code is also provided.