Convolutional Polar Codes: LLR-based Successive Cancellation Decoder and List Decoding Performance

Recently convolutional polar (cpolar) codes have been proposed. A tensor-network-based successive cancellation (SC) decoding was proposed for them under which cpolar codes were shown to outperform polar codes. In this paper we present the notion of m-bit-channels for cpolar codes and give the recursive construction of m-bit-channels for $m=3$. Then a log likelihood ratio(LLR)-based SC decoding of complexity order $\mathcal{O}(Nlog(N))$ for cpolar codes is presented. We also present the numerical results for performance evaluation of cpolar codes under SC list (SCL) decoding. Our simulation results show that cpolar codes can achieve the performance of polar codes with a list size reduced by a factor of 4.