An Enhanced Belief Propagation Decoding Algorithm With Bit-Flipping for Polar Codes

Abstract

For polar codes, bit-flipping strategy can significantly improve the error-correction performance of the belief propagation (BP) decoding. However, the existing BP flipping (BPF) decoding algorithms require many attempts, due to their inefficiency in locating the erroneous positions. This leads to high decoding complexity, limiting their practical applications, especially for long polar codes. In this letter, an enhanced BPF (EBPF) decoding algorithm is proposed. It requires fewer flipping attempts, but yields an advanced decoding performance. By better utilizing the reliability and divergence of bit estimations, a novel weighted metric (WM) is introduced to identify the possible erroneous positions. During each new decoding attempt, the EBPF decoding takes turns to flip these positions. Our simulation results show that, with the same number of flipping attempts, the proposed decoding outperforms the generalized BPF (GBPF) decoding and the state-of-the-art BP correction (BPC) decoding.