Belief propagation (BP) and the concave convex procedure (CCCP) are both
methods that utilize the Bethe free energy as a cost function and solve
information processing tasks. We have developed a new algorithm that also uses
the Bethe free energy, but changes the roles of the master variables and the
slave variables. This is called the Bowman-Levin (BL) approximation in the
domain of statistical physics. When we applied the BL algorithm to decode the
Gallager ensemble of short-length regular low-density parity check codes
(LDPCC) over an additive white Gaussian noise (AWGN) channel, its average
performance was somewhat better than that of either BP or CCCP. This implies
that the BL algorithm can also be successfully applied to other problems to
which BP or CCCP has already been applied.Comment: 2005 IEEE International Symposium on Information Theor