  A lower bound on minimum distance of convolutional polar codes is provided.
The bound is obtained from the minimum weight of generalized cosets of the
codes generated by bottom rows of the polarizing matrix. Moreover, a
construction of convolutional polar subcodes is proposed, which provides
improved performance under successive cancellation list decoding. For
sufficiently large list size, the decoding complexity of convolutional polar
subcodes appears to be lower compared to Arikan polar subcodes with the same
performance. The error probability of successive cancellation list decoding of
convolutional polar subcodes is lower than that of Arikan polar subcodes with
the same list size.
