Refined Belief-Propagation Decoding of Quantum Codes with Scalar Messages

Kao Yueh Kuo, Ching-Yi Lai

研究成果: Paper同行評審

6 引文 斯高帕斯(Scopus)


Codes based on sparse matrices have good performance and can be efficiently decoded by belief-propagation (BP). Decoding binary stabilizer codes needs a quaternary BP for (additive) codes over GF(4), which has a higher check-node complexity compared to a binary BP for codes over GF(2). Moreover, BP decoding of stabilizer codes suffers a performance loss from the short cycles in the underlying Tanner graph. In this paper, we propose a refined BP algorithm for decoding quantum codes by passing scalar messages. For a given error syndrome, this algorithm decodes to the same output as the conventional quaternary BP but with a check-node complexity the same as binary BP. As every message is a scalar, the message normalization can be naturally applied to improve the performance. Another observation is that the message-update schedule affects the BP decoding performance against short cycles. We show that running BP with message normalization according to a serial schedule (or other schedules) may significantly improve the decoding performance and error-floor in computer simulation.

原文American English
出版狀態Published - 12月 2020
事件2020 IEEE Globecom Workshops, GC Wkshps 2020 - Virtual, Taipei, Taiwan
持續時間: 7 12月 202011 12月 2020


Conference2020 IEEE Globecom Workshops, GC Wkshps 2020
城市Virtual, Taipei


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