65 research outputs found
Evading Subspaces Over Large Fields and Explicit List-decodable Rank-metric Codes
We construct an explicit family of linear rank-metric codes over any field F that enables efficient list decoding up to a fraction rho of errors in the rank metric with a rate of 1-rho-eps, for any desired rho in (0,1) and eps > 0. Previously, a Monte Carlo construction of such codes was known, but this is in fact the first explicit construction of positive rate rank-metric codes for list decoding beyond the unique decoding radius.
Our codes are explicit subcodes of the well-known Gabidulin codes, which encode linearized polynomials of low degree via their values at a collection of linearly independent points. The subcode is picked by restricting the message polynomials to an F-subspace that evades certain structured subspaces over an extension field of F. These structured spaces arise from the linear-algebraic list decoder for Gabidulin codes due to Guruswami and Xing (STOC\u2713). Our construction is obtained by combining subspace designs constructed by Guruswami and Kopparty (FOCS\u2713) with subspace-evasive varieties due to Dvir and Lovett (STOC\u2712).
We establish a similar result for subspace codes, which are a collection of subspaces, every pair of which have low-dimensional intersection, and which have received much attention recently in the context of network coding. We also give explicit subcodes of folded Reed-Solomon (RS) codes with small folding order that are list-decodable (in the Hamming metric) with optimal redundancy, motivated by the fact that list decoding RS codes reduces to list decoding such folded RS codes. However, as we only list decode a subcode of these codes, the Johnson radius continues to be the best known error fraction for list decoding RS codes
Bounds on List Decoding of Rank-Metric Codes
So far, there is no polynomial-time list decoding algorithm (beyond half the
minimum distance) for Gabidulin codes. These codes can be seen as the
rank-metric equivalent of Reed--Solomon codes. In this paper, we provide bounds
on the list size of rank-metric codes in order to understand whether
polynomial-time list decoding is possible or whether it works only with
exponential time complexity. Three bounds on the list size are proven. The
first one is a lower exponential bound for Gabidulin codes and shows that for
these codes no polynomial-time list decoding beyond the Johnson radius exists.
Second, an exponential upper bound is derived, which holds for any rank-metric
code of length and minimum rank distance . The third bound proves that
there exists a rank-metric code over \Fqm of length such that the
list size is exponential in the length for any radius greater than half the
minimum rank distance. This implies that there cannot exist a polynomial upper
bound depending only on and similar to the Johnson bound in Hamming
metric. All three rank-metric bounds reveal significant differences to bounds
for codes in Hamming metric.Comment: 10 pages, 2 figures, submitted to IEEE Transactions on Information
Theory, short version presented at ISIT 201
On the List-Decodability of Random Linear Rank-Metric Codes
The list-decodability of random linear rank-metric codes is shown to match
that of random rank-metric codes. Specifically, an -linear
rank-metric code over of rate is shown to be (with high probability)
list-decodable up to fractional radius with lists of size at
most , where is a constant
depending only on and . This matches the bound for random rank-metric
codes (up to constant factors). The proof adapts the approach of Guruswami,
H\aa stad, Kopparty (STOC 2010), who established a similar result for the
Hamming metric case, to the rank-metric setting
List and Probabilistic Unique Decoding of Folded Subspace Codes
A new class of folded subspace codes for noncoherent network coding is
presented. The codes can correct insertions and deletions beyond the unique
decoding radius for any code rate . An efficient interpolation-based
decoding algorithm for this code construction is given which allows to correct
insertions and deletions up to the normalized radius ,
where is the folding parameter and is a decoding parameter. The
algorithm serves as a list decoder or as a probabilistic unique decoder that
outputs a unique solution with high probability. An upper bound on the average
list size of (folded) subspace codes and on the decoding failure probability is
derived. A major benefit of the decoding scheme is that it enables
probabilistic unique decoding up to the list decoding radius.Comment: 6 pages, 1 figure, accepted for ISIT 201
- …
