Iterative joint source-channel decoding with bit flipping

The key of the multimedia compression technique is trying to remove the correlation between the neighboring frames. Due to the computational complexity limitation, considerable correlation is still observed in the multimedia-coded sequence. This residual redundancy can be modeled as a first-order Markov model with the transition probability of the multimedia-coded parameter between adjacent frames. Therefore, in the multimedia transmission over wireless network, there have been researches on the iterative joint source-channel decoding (ISCD), using the transition probability as source side information (SSI) to reduce errors due to the noisy channel. To further correct the errors after the ISCD, we propose a low-complexity yet efficient bit-flipping (BF) algorithm where restrictions are imposed to prevent incurring high undetected error frames. For the ISCD-BF, the source transition probability is crucial to its performance. However, in practice, it is unknown to the receiver. Thus, we propose an SSI estimation to update the transition probability from the output of the ISCD-BF. The performances of the proposed algorithms are examined by applying to a speech transmission over a wireless network. The simulation results show that our proposed algorithms achieve notable gain over the conventional decoder.