Successive Cancellation Priority Decoding of Polar Codes

Abstract

The successive cancellation list (SCL) decoding of polar codes can achieve a performance close to that of maximum-likelihood decoding. Nevertheless, a large list size results in high-computational complexity. In this paper, a successive cancellation priority (SCP) decoding algorithm is proposed to reduce the time complexity. The SCP decoder performs a priority-first decoding, which is composed of a priority queue and a trellis. During the SCP decoding, the priority queue interacts with the trellis iteratively. Conceptually, the priority queue stores the priority information and guides the extension of the candidate path. The trellis calculates and stores the intermediate results. Since most of the unnecessary path extensions are avoided by using the priority queue, the time complexity of the SCP decoder is much lower than that of the standard SCL decoder. Then, a quantized priority queue is introduced to avoid the comparison operations in the path selection and to simplify the SCP decoder. Furthermore, we prove that the path extension of the SCP decoder is equivalent to the extension of the most reliable paths of the standard SCL decoder. Thus, the SCP decoder can achieve the same decoding performance as that of the standard SCL decoder.