Impact of Linear Prediction Coefficients on Totally Blind APP Channel Estimation

Totally blind APP channel estimation is based on the A Posteriori Probability (APP) calculation algorithm. Asymmetrical modulation schemes are used in order to resolve the phase ambiguity with no need for any pilot or reference symbols. In OFDM-systems, the two-dimensional channel estimation is performed by applying a concatenation of two one-dimensional APP estimators for frequency and time direction in combination with an iterative estimation and decoding loop. Linear filters are used to predict the channel transfer function while traversing the trellis of the APP estimator. In this paper, we study the influence which the coefficients of these predictors have on the channel estimation result. We compare the performance of ideal predictors with the performance of predictors with coefficients based on optimal channel statistics and averaging. We study the behavior of the the iterative estimation and decoding loop using the Extrinsic Information Transfer (EXIT) Chart and evaluate the performance of the algorithm with respect to the BER.