{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/decoder-tailored-polar-code-design-using-the","title":"Decoder-tailored Polar Code Design Using the Genetic Algorithm","arxiv_id":"1901.10464","date":"2019-01-28","proceeding":null,"authors":["Ahmed Elkelesh","Moustafa Ebada","Sebastian Cammerer","Stephan ten Brink"],"abstract":"We propose a new framework for constructing polar codes (i.e., selecting the\nfrozen bit positions) for arbitrary channels, and tailored to a given decoding\nalgorithm, rather than based on the (not necessarily optimal) assumption of\nsuccessive cancellation (SC) decoding. The proposed framework is based on the\nGenetic Algorithm (GenAlg), where populations (i.e., collections) of\ninformation sets evolve successively via evolutionary transformations based on\ntheir individual error-rate performance. These populations converge towards an\ninformation set that fits both the decoding behavior and the defined channel.\nUsing our proposed algorithm over the additive white Gaussian noise (AWGN)\nchannel, we construct a polar code of length 2048 with code rate 0.5, without\nthe CRC-aid, tailored to plain successive cancellation list (SCL) decoding,\nachieving the same error-rate performance as the CRC-aided SCL decoding, and\nleading to a coding gain of 1 dB at BER of $10^{-6}$. Further, a belief\npropagation (BP)-tailored construction approaches the SCL error-rate\nperformance without any modifications in the decoding algorithm itself. The\nperformance gains can be attributed to the significant reduction in the total\nnumber of low-weight codewords. To demonstrate the flexibility, coding gains\nfor the Rayleigh channel are shown under SCL and BP decoding. Besides\nimprovements in error-rate performance, we show that, when required, the GenAlg\ncan be also set up to reduce the decoding complexity, e.g., the SCL list size\nor the number of BP iterations can be reduced, while maintaining the same\nerror-rate performance.","url_abs":"http://arxiv.org/abs/1901.10464v1","url_pdf":"http://arxiv.org/pdf/1901.10464v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"decoder-tailored-polar-code-design-using-the","repo_url":"https://github.com/AhmedElkelesh/Genetic-Algorithm-based-Polar-Code-Construction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"2048","task_name":"Playing the Game of 2048"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}