English

ORCAS Codes: A Flexible Generalization of Polar Codes with Low-Complexity Decoding

Information Theory 2025-10-14 v2 Signal Processing math.IT

Abstract

Motivated by the need for channel codes with low-complexity soft-decision decoding algorithms, we consider the recursive Plotkin concatenation of optimal low-rate and high-rate codes based on simplex codes and their duals. These component codes come with low-complexity maximum likelihood (ML) decoding which, in turn, enables efficient successive cancellation (SC)-based decoding. As a result, the proposed optimally recursively concatenated simplex (ORCAS) codes achieve a performance that is at least as good as that of polar codes. For practical parameters, the proposed construction significantly outperforms polar codes in terms of block error rate by up to 0.5 dB while maintaining similar decoding complexity. Furthermore, the codes offer greater flexibility in codeword length than conventional polar codes.

Keywords

Cite

@article{arxiv.2508.09744,
  title  = {ORCAS Codes: A Flexible Generalization of Polar Codes with Low-Complexity Decoding},
  author = {Andreas Zunker and Marvin Rübenacke and Stephan ten Brink},
  journal= {arXiv preprint arXiv:2508.09744},
  year   = {2025}
}

Comments

7 pages, 2 figures. Accepted for publication at the 2025 IEEE Global Communications Conference (GLOBECOM)

R2 v1 2026-07-01T04:48:01.698Z