Blind Equalization Via Sample Sorting

We present a computationally efficient blind equalization technique to mitigate the effects of inter-symbol interference (ISI). Our technique is based entirely on context sorting of received ISI corrupted samples of a communications system. Techniques based on rank sorting and successive rank sorting provide context based analysis of the underlying state transitions of a finite memory source channel. We are able to exploit this information to effectively perform blind equalization and moreover recover the transmitted symbols of an ISI corrupted data stream