SOLOS: Soft-Output List Ordered Statistics Decoding for Product Codes

Turbo product codes have emerged as promising candidate channel codes for hyper-reliable low-latency communication scenarios owing to the inherent parallelism of product code decoding. Recently proposed product-coded MIMO systems with polar component codes demonstrate both performance gains and latency reductions compared to traditional 1-D coded systems. However, the existing successive cancellation list (SCL)-based decoding algorithm in polar-product-coded MIMO systems suffers from high memory costs due to storing internal LLRs and still exhibits potential for further performance improvements. To enhance the performance of product-coded MIMO systems and alleviate storage overhead, this paper investigates decoding schemes based on list ordered statistics decoding (List-OSD). A hardware-friendly soft-output computation method for List-OSD is proposed, which exploits both candidate codewords and pruned paths generated during decoding. Two soft-output list ordered statistics (SOLOS) decoding schemes are presented, respectively incorporating the Pyndiah method and the proposed soft-output computation technique. Simulation results show that the two proposed decoding schemes outperform conventional decoders across various code rates and constructions in product-coded MIMO systems. For the (64, 42)2 polar-product code, the proposed decoders with a list size of 32 achieve a 0.4 dB performance gain over the SCL-based decoder with a list size of 8 at comparable latency, while reducing the byte-level memory usage by 51.2%.