Lowering the Error Floor of Error Correction Code Transformer

Abstract: With the success of transformer architectures across diverse applications, the error correction code transformer (ECCT) has gained significant attention for its superior decoding performance. In spite of its advantages, the error floor phenomenon in ECCT decoding remains unexplored. We present the first investigation of the error floor issue in ECCT and propose a hybrid decoding approach that integrates hard decision decoders as pre- and post-decoders with ECCT to effectively lower the error floor. In particular, we introduce a novel loss function for ECCT that considers the dynamics of hybrid decoding algorithm. Training ECCT with the proposed loss function enhances its ability to correct specific error patterns by taking into account its interaction with the auxiliary decoders. Simulation results demonstrate that the proposed hybrid decoder with the novel loss function significantly outperforms the original ECCT in both the waterfall and the error floor regions.