论文标题
用自适应高斯消除简短代码的订购统计量解码
Ordered-Statistics Decoding with Adaptive Gaussian Elimination Reduction for Short Codes
论文作者
论文摘要
在本文中，我们提出了一种有效的有序统计解码（OSD）算法，并具有自适应高斯消除（GE）还原技术。提出的解码器利用两个解码条件自适应地删除OSD中的GE。第一个条件通过估计解码误差概率来确定是否可以在OSD过程中跳过GE。然后，使用第二个条件在没有GE的情况下在解码过程中识别正确的解码结果。所提出的解码器可以打破GE开销引入的OSD解码器中的``复杂度地板''。仿真结果建议，与文献中最新的方案相比，所提出的方法可以显着降低高SNR的解码复杂性，而误差校正能力中没有任何降解。
In this paper, we propose an efficient ordered-statistics decoding (OSD) algorithm with an adaptive Gaussian elimination (GE) reduction technique. The proposed decoder utilizes two decoding conditions to adaptively remove GE in OSD. The first condition determines whether GE could be skipped in the OSD process by estimating the decoding error probability. Then, the second condition is utilized to identify the correct decoding result during the decoding process without GE. The proposed decoder can break the ``complexity floor'' in OSD decoders introduced by the GE overhead. Simulation results advise that when compared with the latest schemes in the literature, the proposed approach can significantly reduce the decoding complexity at high SNRs without any degradation in the error-correction capability.
