Abstract
The ordered statistic decoding (OSD) algorithm for short-length linear block codes provides an attractive ML-approaching performance, expected to be used for the ultra-reliable low latency communication (URLLC) at the next-generation wireless solutions. To find the corrected codeword among numerous candidates, however, the decoding process requires a considerable amount of computational costs, which need to be simplified to achieve low-latency processing. In this letter, we present several schemes that relax the overall complexity of the state-of-the-art segmentation discarding algorithm. Without degrading the error-correcting power, our method approximate the internal steps for computing the segment sizes and the stopping bounds at the run time, reducing the average processing costs by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.6\times 10 ^{4}$ </tex-math></inline-formula> times for achieving the low-BLER performance.
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