Blind Iterative Decoding of Side-informed Data Hiding Using the Expectation-Maximization Algorithm

摘要

Distortion-Compensated Dither Modulation (DC-DM), also known as Scalar Costa Scheme (SCS), has been theoretically shown to be near-capacity achieving thanks to its use of side information at the encoder. In practice, channel coding is needed in conjunction with this quantization-based scheme in order to approach the achievable rate limit. The most powerful coding methods use iterative decoding (turbo codes, LDPC), but they require knowledge of the channel model. Previous works on the subject have assumed the latter to be known by the decoder. We investigate here the possibility of undertaking blind iterative decoding of DC-DM, using maximum likelihood estimation of the channel model within the decoding procedure. The unknown attack is assumed to be i.i.d. and additive. Before each iterative decoding step, a new optimal estimation of the attack model is made using the reliability information provided by the previous step. This new model is used for the next iterative decoding stage, and the procedure is repeated until convergence. We show that the iterative Expectation-Maximization algorithm is suitable for solving the problem posed by model estimation, as it can be conveniently intertwined with iterative decoding.