Channel order estimation via sample sorting

We present a computationally efficient channel order estimation technique that can be used as a first step in blind channel estimation and equalization. Our approach is based entirely on context sorting inter-symbol interference corrupted samples. This leads to high computational efficiency when compared to other standard techniques that rely on second-order correlation statistics. In addition to demonstrating the computational efficiency of our approach we also show that it has superior estimation performance in comparison to other techniques presented in the literature in recent years.