TY - GEN

T1 - Efficiently decoding Reed-Muller codes from random errors

AU - Saptharishi, Ramprasad

AU - Shpilka, Amir

AU - Volk, Ben Lee

N1 - Publisher Copyright: © 2016 ACM.

PY - 2016/6/19

Y1 - 2016/6/19

N2 - Reed-Muller codes encode an m-variate polynomial of degree r by evaluating it on all points in {0, 1}m. We denote this code by RM(m,r). The minimal distance of RM(m,r) is 2m-r and so it cannot correct more than half that number of errors in the worst case. For random errors one may hope for a better result. In this work we give an efficient algorithm (in the block length n = 2m) for decoding random errors in Reed-Muller codes far beyond the minimal distance. Specifically, for low rate codes (of degree r = o(√m)) we can correct a random set of (1/2 - o(1))n errors with high probability. For high rate codes (of degree m - r for r = o(√m/log m)), we can correct roughly mr/2 errors. More generally, for any integer r, our algorithm can correct any error pattern in RM(m, m - (2r + 2)) for which the same erasure pattern can be corrected in RM(m, m-(r+1)). The results above are obtained by applying recent results of Abbe, Shpilka and Wigderson (STOC, 2015), Kumar and Pfister (2015) and Kudekar et al. (2015) regarding the ability of Reed-Muller codes to correct random erasures. The algorithm is based on solving a carefully defined set of linear equations and thus it is significantly different than other algorithms for decoding Reed-Muller codes that are based on the recursive structure of the code. It can be seen as a more explicit proof of a result of Abbe et al. that shows a reduction from correcting erasures to correcting errors, and it also bares some similarities with the famous Berlekamp-Welch algorithm for decoding Reed-Solomon codes.

AB - Reed-Muller codes encode an m-variate polynomial of degree r by evaluating it on all points in {0, 1}m. We denote this code by RM(m,r). The minimal distance of RM(m,r) is 2m-r and so it cannot correct more than half that number of errors in the worst case. For random errors one may hope for a better result. In this work we give an efficient algorithm (in the block length n = 2m) for decoding random errors in Reed-Muller codes far beyond the minimal distance. Specifically, for low rate codes (of degree r = o(√m)) we can correct a random set of (1/2 - o(1))n errors with high probability. For high rate codes (of degree m - r for r = o(√m/log m)), we can correct roughly mr/2 errors. More generally, for any integer r, our algorithm can correct any error pattern in RM(m, m - (2r + 2)) for which the same erasure pattern can be corrected in RM(m, m-(r+1)). The results above are obtained by applying recent results of Abbe, Shpilka and Wigderson (STOC, 2015), Kumar and Pfister (2015) and Kudekar et al. (2015) regarding the ability of Reed-Muller codes to correct random erasures. The algorithm is based on solving a carefully defined set of linear equations and thus it is significantly different than other algorithms for decoding Reed-Muller codes that are based on the recursive structure of the code. It can be seen as a more explicit proof of a result of Abbe et al. that shows a reduction from correcting erasures to correcting errors, and it also bares some similarities with the famous Berlekamp-Welch algorithm for decoding Reed-Solomon codes.

KW - Error correcting codes

KW - Random errors

KW - Reed-Muller

UR - http://www.scopus.com/inward/record.url?scp=84979243386&partnerID=8YFLogxK

U2 - https://doi.org/10.1145/2897518.2897526

DO - https://doi.org/10.1145/2897518.2897526

M3 - منشور من مؤتمر

T3 - Proceedings of the Annual ACM Symposium on Theory of Computing

SP - 227

EP - 235

BT - STOC 2016 - Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing

A2 - Mansour, Yishay

A2 - Wichs, Daniel

T2 - 48th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2016

Y2 - 19 June 2016 through 21 June 2016

ER -