A Construction of Turbo-Like Codes for Iterative Channel Estimation Based on Probabilistic Bias

A novel signaling scheme for iterative channel estimation and data decoding is proposed. In the proposed scheme, the occurrence probability of transmitted symbols is biased. A priori information about the bias is utilized for the initial channel estimation. The proposed scheme is based on parallel concatenation of two biased convolutional codes (BCCs), which are constructed as systematic recursive convolutional codes with state-dependent puncturing. The BCCs can be regarded as a joint coding scheme that determines the insertion positions of pilot symbols according to information bits. The proposed scheme is numerically shown to outperform conventional pilot-based schemes in the waterfall region, while it is inferior to the conventional schemes in the error-floor region.