Abstract
Polar codes are one of the most favorable capacity-achieving codes owing to their simple structures and low decoding complexity. Successive cancellation list (SCL) decoders with large list sizes achieve performances very close to those of maximum-likelihood (ML) decoders. However, hardware cost is a severe problem because an SCL decoder with list size L consists of L copies of a successive cancellation (SC) decoder. To address this issue, a stochastic SCL (SSCL) polar decoder is proposed. Although stochastic computing can achieve a good hardware reduction compared with the deterministic one, its straightforward application to an SCL decoder is not well-suited owing to the precision loss and severe latency. Therefore, a doubling probability approach and adaptive distributed sorting (DS) are introduced. A corresponding hardware architecture is also developed. Field programmable gate array (FPGA) results demonstrate that the proposed stochastic SCL polar decoder can achieve a good performance and complexity tradeoff.
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Acknowledgements
This work was supported in part by National Key R&D Program of China (Grant No. 2020YFB220-5503), National Natural Science Foundation of China (Grant Nos. 61871115, 61501116), Jiangsu Provincial NSF for Excellent Young Scholars (Grant No. BK20180059), Six Talent Peak Program of Jiangsu Province (Grant No. 2018-DZXX-001), Distinguished Perfection Professorship of Southeast University, Fundamental Research Funds for the Central Universities, and Student Research Training Program of Southeast University.
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Liang, X., Wang, H., Shen, Y. et al. Efficient stochastic successive cancellation list decoder for polar codes. Sci. China Inf. Sci. 63, 202303 (2020). https://doi.org/10.1007/s11432-019-2924-6
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DOI: https://doi.org/10.1007/s11432-019-2924-6