Folded Tree Maximum-Likelihood Decoder for Kronecker Product-Based Codes

In this paper, we propose efficient maximum-likelihood (ML) decoding for binary Kronecker product-based (KPB) codes. This class of codes, have a matrix defined by the n-fold iterated Kronecker product G(n) = F-circle times n of a binary upper-triangular kernel matrix F, where some columns are suppressed given a specific puncturing pattern. Polar and Reed-Muller codes are well known examples of such KPB codes.