High-throughput Low-latency Hardware Implementation of BCH Decoders

Computer Science > Information Theory [Submitted on 16 Jun 2026] Title:High-throughput Low-latency Hardware Implementation of BCH Decoders View PDF HTML (experimental)Abstract:Two well-known decoding algorithms for BCH codes are conventional decoding, based on the Berlekamp-Massey algorithm in combination with Chien search, and direct decoding, which uses direct solutions to find the error locator polynomial and its roots. We introduce hardware architectures for conventional and direct decoding of extended BCH codes. Both architectures support implementation for any blocklength. Our conventional decoder supports any error-correction capability, whereas direct decoding is supported up to error correcting capability t = 4. To the best of our knowledge, our work is the first to implement a direct BCH decoder with an error-correction capability 4. We synthesize for the Xilinx Ultrascale+ XCZU48DR field-programmable gate-array and 16 nm FinFET for blocklengths up to 1024 bits and t = 4. We show that the direct decoder outperforms the conventional decoder in area efficiency for t = 2, t = 3, and for t = 4 for blocklengths longer than 256. Post-synthesis results for 16 nm FinFET show codeword per clock-cycle throughput at 1 GHz, achieving 239 Gb/s for the (256, 239) eBCH code and 223 Gb/s for (256, 223) eBCH code at 2 ns and 8 ns latency, respectively. Current browse context: cs.IT References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer (What is the Explorer?) Connected Papers (What is Connected Papers?) Litmaps (What is Litmaps?) scite Smart Citations (What are Smart Citations?) Code, Data and Media Associated with this Article alphaXiv (What is alphaXiv?) CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub (What is DagsHub?) Gotit.pub (What is GotitPub?) Hugging Face (What is Huggingface?) ScienceCast (What is ScienceCast?) Demos Recommenders and Search Tools Influence Flower (What are Influence Flowers?) CORE Recommender (What is CORE?) arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.