A novel algorithm for adaptive reduced-complexity blind maximum likelihood sequence estimation (MLSE) is proposed.Basic idea behind the proposed algorithm is the principle of per-survivor processing (PSP) and the adaptive selection of survivor path.The key feature of the proposed algorithm is that the minimum Euclidean distance in the trellis can adaptively be estimated

and then only a small number of the most likely survivors in the trellis are retained and utilized for joint channel and data estimation.Theoretical analysis and computer simulation results show that

for channels with severe intersymbol interference (ISI)

the proposed algorithm has higher performance in symbol error rate and lower computational complexity at high signal-to-noise ratios (SNR).