Fast SC-Flip Decoding of Polar Codes with Reinforcement Learning

In this paper, we introduce a novel bit-flipping algorithm for fast successive cancellation (FSC) decoding of polar codes. In particular, we first propose a new bit-flipping strategy tailored to single parity-check (SPC) constituent codes of polar codes. A parameterized bit-flipping model is then developed and reinforcement learning (RL) is used to optimize the parameters. Our experimental results show that for a polar code of length 512 with 256 information bits, the proposed decoder has a better or similar error-correction performance compared to the state-of-the-art fast DSCF (FDSCF) decoding algorithm when the same number of maximum decoding attempts is considered.