Sequential Polar Decoding with Cost Metric Threshold

Polar codes have established themselves as a cornerstone in modern error correction coding due to their capacity-achieving properties and practical implementation advantages. However, decoding polar codes remains a computationally intensive task. In this paper, we introduce a novel approach to improve the decoding efficiency of polar codes by integrating the threshold-based SC-Creeper decoding algorithm, originally designed for convolutional codes. Our proposed decoder with an additional cost function seamlessly merges two established decoding paradigms, namely the stack and Fano approaches. The core idea is to leverage the strengths of both decoding techniques to strike a balance between computational efficiency and performance, with an additional method of controlling movement along a code tree. Simulations demonstrate the superiority of the proposed improved SC-Creeper decoder with tuned parameters. The improved SC-Creeper decoder achieves the performance of the CA-SCL-8 decoder in terms of high code rates and overcomes it in terms of the $N=1024$ code length, while simultaneously surpassing the efficiency of the traditional Fano decoding algorithm.