Capacity-Constrained Rate Profiling Refinement for PAC Codes via Bit Position Reassignment

Abstract

Polarization-Adjusted Convolutional (PAC) codes combine the polarization effect of polar codes with the memory structure of convolutional precoding, offering strong error-correcting performance. However, the performance of PAC codes heavily depends on the selection of information set. Existing rate profiling methods such as Reed Muller-Polar (RM-Polar) may inadvertently assign an excessively large information set to low-capacity bit-channels. This tends to result in degraded decoding performance especially when using decoders with small to moderate list sizes. This letter proposes a rate profiling refinement strategy for PAC codes that reassigns certain information and frozen bit positions to better match the underlying channel capacity. Simulation results indicate that the proposed strategy significantly improves the decoding performance of PAC codes over various code rates.