Bias-based training for iterative channel estimation and data decoding in fast fading channels

A novel signaling scheme is proposed for iterative channel estimation and data decoding in fast fading channels. The basic idea is to bias the occurrence probability of transmitted symbols. A priori information about the bias is utilized for channel estimation. The bias-based scheme is constructed as a serially concatenated code, in which a convolutional code and a biased nonlinear block code are used as the outer and inner codes, respectively. This construction allows the receiver to estimate channel state information (CSI) efficiently. The proposed scheme is numerically shown to outperform conventional pilot-based schemes in terms of spectral efficiency for moderately fast fading channels.