  In this paper we investigate stopping criteria for iterative decoding from a
mutual information perspective. We introduce new iteration stopping rules based
on an approximation of the mutual information between encoded bits and decoder
soft output. The first type stopping rule sets a threshold value directly on
the approximated mutual information for terminating decoding. The threshold can
be adjusted according to the expected bit error rate. The second one adopts a
strategy similar to that of the well known cross-entropy stopping rule by
applying a fixed threshold on the ratio of a simple metric obtained after each
iteration over that of the first iteration. Compared with several well known
stopping rules, the new methods achieve higher efficiency.
