An Optimized Belief Propagation List Decoding for Polar Codes with Dynamic Flipping

In the context of polar codes, belief propagation list (BPL) decoding has demonstrated a substantial enhancement in parallel decoding performance, achieving high throughput.Nevertheless, a performance gap still exists between the advanced BPL decoding and successive cancellation list (SCL) decoding methods.Moreover, existing bit-flipping strategies are inefficient in accurately identifying erroneous bit positions, leading to elevated computational complexity and limiting their practical applicability.This study introduces an optimized BPL decoding algorithm with dynamic flipping (OBPL-DF) aimed at bridging this performance gap while reducing computational demands.Initially, an efficient decoding scheme is proposed to further decrease computational complexity in practical scenarios.Subsequently, to improve the precision of error position detection, a partial cyclic redundancy check (CRC) code is employed on erroneous codewords.Finally, a dynamic flipping metric is developed within the bit-flipping strategy, allowing the selection of flipped positions to be guided by this novel metric rather than being confined to a predetermined set.Simulation results demonstrate that the OBPL-DF algorithm surpasses the performance of existing BPL flip (BPLF) decoding techniques and approaches that of enhanced SCL decoding, all while achieving significantly lower latency.