For the scenarios with high throughput requirements, the belief propagation (BP) decoding is one of the most promising decoding strategies for polar codes. By pruning the redundant variable nodes (VNs) and check nodes (CNs) in the original factor graph, the graph is condensed to a sparse bipartite graph that is similar to the graph for low-density parity-check (LDPC) codes. In this paper, we introduce the bit flipping scheme into the LDPC-like BP (L-BP) decoding and propose two methods to identify the error-prone VNs. By additional decoding attempts, the L-BP flip (L-BPF) decoding improves the error-correction performance with a similar average complexity for high E_b/N₀ values. The simulation results show that the L-BPF decoding achieves 0.25 dB gain compared with the L-BP decoding. Finally, a parallel decoder with the proposed L-BPF algorithm for an (256,128) polar code is implemented using 65nm CMOS technology, and it delivers a throughput of 1877.3 Mbps.

对于具有高吞吐量要求的场景，置信传播（BP）解码是极性码最有前途的解码策略之一。通过修剪原始因子图中的冗余变量节点（VNs）和校验节点（CNs），该图被压缩为一个稀疏的二部图，类似于低密度奇偶校验（LDPC）码的图。在本文中，我们将比特翻转方案引入类 LDPC BP (L-BP) 解码，并提出了两种方法来识别容易出错的 VN。通过额外的解码尝试，L-BP 翻转 (L-BPF) 解码提高了纠错性能，对于高E _b / N ₀具有类似的平均复杂度值。仿真结果表明，与L-BP解码相比，L-BPF解码实现了0.25 dB的增益。最后，使用 65 纳米 CMOS 技术实现了具有建议的 (256,128) 极性码的 L-BPF 算法的并行解码器，其吞吐量为 1877.3 Mbps。