Blind equalization of switching channels by ICA and learning of learning rate

In the literature of blind equalization, algorithms developed for equalizing an SISO or SIMO channel fail sometimes when the channel condition is poor. We derive blind equalization algorithms from blind separation algorithms to equalize the SISO channel with fractionally sampling. The approach is also applied to equalize SIMO or MIMO channels. For switching channels, we use an updating rule to tune the learning rate of on-line algorithms automatically to follow the channel change. The idea is applicable to improve all blind equalization algorithms to equalize switching channels.