Extremal Problems of Information Combining

In this paper, we study moments of soft bits of binary-input symmetric-output channels and solve some extremal problems of the moments. We use these results to solve the extremal information combining problem. Further, we extend the information combining problem by adding a constraint on the second moment of soft bits, and find the extremal distributions for this new problem. The results for this extension problem are used to improve the prediction of convergence of the belief propagation decoding of low-density parity-check (LDPC) codes, provided that another extremal problem related to the variable nodes is solved.