ScholarWorks@중앙대학교

초록

Polarization-Adjusted Convolutional (PAC) codes achieve near-capacity performance at short block lengths, yet their error-correction capability depends strongly on where frozen bits are placed. The conventional Reed-Muller rule works well when a Successive Cancellation List (SCL) decoder can employ a large list, but it loses effectiveness when the list size must remain small. We introduce an alternative rate-profiling method that ranks bit positions by the average magnitude of their log-likelihood ratios collected in advance and designates the least reliable positions as frozen. Simulations of a PAC code with block length one hundred twenty-eight and rate one half over an additive white Gaussian noise channel show that the proposed profile yields lower bit- and frame-error rates than the Reed-Muller rule for list sizes up to sixteen, although its performance stops improving for larger lists. These results indicate that the LLR-based profile is a practical choice when decoder complexity limits the list size.

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