Iterative channel estimation and decoding is commonly used in the receivers for communication over fading channels. In this scheme the computationally expensive soft-output decoding is executed during every iteration. We suggest a simpler alternative procedure to compute the feedback soft values for channel re-estimation during the intermediate iterations. This procedure can be used with any monomial code.

Recursive list decoding is considered for Reed-Muller (RM) codes. The algorithm repeatedly relegates itself to the shorter RM codes by recalculating the posterior probabilities of their symbols. Intermediate decodings are only performed when these recalculations reach the trivial RM codes. In turn, the updated lists of most plausible codewords are used in subsequent decodings. The algorithm is further improved by using permutation techniques on code positions and by eliminating the most error-prone information bits. Simulation results show that for all RM codes of length 256 and many subcodes of length 512, these algorithms approach maximum-likelihood (ML) performance within a margin of 0.1 dB. As a result, we present tight experimental bounds on ML performance for these codes