Partially Permuted Multi-Trellis Belief Propagation for Polar Codes
Vismika Ranasinghe, Nandana Rajatheva, Matti Latva-aho

TL;DR
This paper introduces a novel partially permuted multi-trellis belief propagation decoder for polar codes that improves error performance and reduces latency by permuting only subgraphs of the factor graph.
Contribution
It proposes a new variant of multi-trellis BP decoding that permutes subgraphs, retaining variable node information and enhancing decoding efficiency.
Findings
0.25 dB error performance gain at FER of 10^(-6)
Reduced number of iterations compared to full permutation decoder
Improved mitigation of cycles causing oscillation errors
Abstract
Belief propagation (BP) is an iterative decoding algorithm for polar codes which can be parallelized effectively to achieve higher throughput. However, because of the presence of error floor due to cycles and stopping sets in the factor graph, the performance of the BP decoder is far from the performance of state of the art cyclic redundancy check (CRC) aided successive cancellation list (CA-SCL) decoders. It has been shown that successive BP decoding on multiple permuted factor graphs, which is called the multi-trellis BP decoder, can improve the error performance. However, when permuting the entire factor graph, since the decoder dismisses the information from the previous permutation, the number of iterations required is significantly larger than that of the standard BP decoder. In this work, we propose a new variant of the multi-trellis BP decoder which permutes only a subgraph of…
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