Recently, a cluster-based maximum-likelihood sequence estimator (MLSE)
for nonlinear channels was described, which consists of a clustering
network and an MLSE implemented by the Viterbi algorithm [6]. The clus
ter-based MLSE can be used for digital communication through nonlinear
finite-length channels because channel mapping estimation is used ins
tead of channel estimation in the conventional MLSE. The clustering ne
twork of the cluster-based MLSE, which estimates the channel mapping b
etween the signal input vectors and the noiseless channel outputs, is
a supervised network and requires a training sequence. In this paper,
we propose a blind channel mapping estimator to estimate the channel m
apping without using the training sequence, The blind channel mapping
estimator has a clustering block and a mapping block, The clustering b
lock estimates the channel outputs, which represent the channel mappin
g, subject to an unknown permutation operation because no training seq
uence is utilized, That permutation operation is resolved by the mappi
ng block, and therefore, the channel mapping is obtained, Introducing
the blind channel mapping estimator into the cluster-based MLSE, a bli
nd cluster-based MLSE for nonlinear channels can be done. Computer sim
ulations of the blind channel mapping estimator and the blind MLSE for
nonlinear channels are presented.