Method for detection and iterative decoding with reduced complexity of coded and interleaved symbols transmitted over a transmission channel, these symbols being transmitted from a sequence of binary symbols, each sequence of symbols received comprising at least, in addition to the data, guard and tail symbols, specific learning symbols, characterized in that it consists, from a suboptimal equalizer with weighted inputs and outputs, working on a channel lattice reduced in terms of number of states: • prior to any iteration, - in performing an initial linear estimation of the coefficients of the impulse response of the transmission channel H ^ z l from the specific learning symbols transmitted; • by iteration, for each current iteration: - in performing a suboptimal equalization working on a channel lattice reduced in terms of number of states from an a priori item of information on the symbol bits deriving from the decoding of the prior iteration; - in performing a decoding with weighted inputs and outputs from an a priori item of information on the coded bits originating from the suboptimal equalization operation of the current iteration, - in performing an updated iterative re-estimation of the coefficients of the impulse response of the transmission channel, according to the items of information delivered by the iterative equalization and decoding process, - in repeating the steps performed by iteration on the next iteration. • prior to any iteration, - in performing an initial linear estimation of the coefficients of the impulse response of the transmission channel H ^ z l from the specific learning symbols transmitted; - in performing an initial linear estimation of the coefficients of the impulse response of the transmission channel H ^ z l from the specific learning symbols transmitted; • by iteration, for each current iteration: - in performing a suboptimal equalization working on a channel lattice reduced in terms of number of states from an a priori item of information on the symbol bits deriving from the decoding of the prior iteration; - in performing a decoding with weighted inputs and outputs from an a priori item of information on the coded bits originating from the suboptimal equalization operation of the current iteration, - in performing an updated iterative re-estimation of the coefficients of the impulse response of the transmission channel, according to the items of information delivered by the iterative equalization and decoding process, - in repeating the steps performed by iteration on the next iteration. - in performing a suboptimal equalization working on a channel lattice reduced in terms of number of states from an a priori item of information on the symbol bits deriving from the decoding of the prior iteration; - in performing a decoding with weighted inputs and outputs from an a priori item of information on the coded bits originating from the suboptimal equalization operation of the current iteration, - in performing an updated iterative re-estimation of the coefficients of the impulse response of the transmission channel, according to the items of information delivered by the iterative equalization and decoding process, - in repeating the steps performed by iteration on the next iteration.