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 $\mathbb{F}_q$-linear rank-metric code over $\mathbb{F}_q^{m \times n}$ of rate $R = (1-\rho)(1-\frac{n}{m}\rho)-\varepsilon$ is shown to be (with high probability) list-decodable up to fractional radius $\rho \in (0,1)$ with lists of size at most $\frac{C_{\rho,q}}{\varepsilon}$, where $C_{\rho,q}$ is a constant depending only on $\rho$ and $q$. 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

Subspace Designs Based on Algebraic Function Fields

Subspace designs are a (large) collection of high-dimensional subspaces {H_i} of F_q^m such that for any low-dimensional subspace W, only a small number of subspaces from the collection have non-trivial intersection with W; more precisely, the sum of dimensions of W cap H_i is at most some parameter L. The notion was put forth by Guruswami and Xing (STOC\u2713) with applications to list decoding variants of Reed-Solomon and algebraic-geometric codes, and later also used for explicit rank-metric codes with optimal list decoding radius. Guruswami and Kopparty (FOCS\u2713, Combinatorica\u2716) gave an explicit construction of subspace designs with near-optimal parameters. This construction was based on polynomials and has close connections to folded Reed-Solomon codes, and required large field size (specifically q >= m). Forbes and Guruswami (RANDOM\u2715) used this construction to give explicit constant degree "dimension expanders" over large fields, and noted that subspace designs are a powerful tool in linear-algebraic pseudorandomness. Here, we construct subspace designs over any field, at the expense of a modest worsening of the bound $L$ on total intersection dimension. Our approach is based on a (non-trivial) extension of the polynomial-based construction to algebraic function fields, and instantiating the approach with cyclotomic function fields. Plugging in our new subspace designs in the construction of Forbes and Guruswami yields dimension expanders over F^n for any field F, with logarithmic degree and expansion guarantee for subspaces of dimension Omega(n/(log(log(n))))

Lossless Dimension Expanders via Linearized Polynomials and Subspace Designs

For a vector space F^n over a field F, an (eta,beta)-dimension expander of degree d is a collection of d linear maps Gamma_j : F^n -> F^n such that for every subspace U of F^n of dimension at most eta n, the image of U under all the maps, sum_{j=1}^d Gamma_j(U), has dimension at least beta dim(U). Over a finite field, a random collection of d = O(1) maps Gamma_j offers excellent "lossless" expansion whp: beta ~~ d for eta >= Omega(1/d). When it comes to a family of explicit constructions (for growing n), however, achieving even modest expansion factor beta = 1+epsilon with constant degree is a non-trivial goal. We present an explicit construction of dimension expanders over finite fields based on linearized polynomials and subspace designs, drawing inspiration from recent progress on list-decoding in the rank-metric. Our approach yields the following: - Lossless expansion over large fields; more precisely beta >= (1-epsilon)d and eta >= (1-epsilon)/d with d = O_epsilon(1), when |F| >= Omega(n). - Optimal up to constant factors expansion over fields of arbitrarily small polynomial size; more precisely beta >= Omega(delta d) and eta >= Omega(1/(delta d)) with d=O_delta(1), when |F| >= n^{delta}. Previously, an approach reducing to monotone expanders (a form of vertex expansion that is highly non-trivial to establish) gave (Omega(1),1+Omega(1))-dimension expanders of constant degree over all fields. An approach based on "rank condensing via subspace designs" led to dimension expanders with beta >rsim sqrt{d} over large fields. Ours is the first construction to achieve lossless dimension expansion, or even expansion proportional to the degree

Bounded-degree Low Rank Parity Check Codes

Low rank parity check (LRPC) codes are the rank-metric analogue of low density parity check codes. In this paper we investigate a sub-family of LRPC codes, which have a parity check matrix defined over a subspace $V_{\alpha,d}=\langle 1,\alpha, \ldots, \alpha^{d-1}\rangle_{\mathbb{F}_q}\subsetneq \mathbb{F}_{q^m}$, where $\mathbb{F}_{q^m}$ is the finite field of $q^m$ elements and $d$ is significantly smaller than $m$. These codes are named bounded-degree LRPC (BD-LRPC) codes and are the same as the standard LRPC codes of density $2$ when the degree $d=2$, while BD-LRPC codes of degree $d>2$ constitute a proper subset of LRPC codes of density $d$. Exploiting the particular structure of their parity check matrix, we show that the BD-LRPC codes of degree $d$ can uniquely correct errors of rank weight $r$ when $n-k \geq r + u$ for certain $u \geq 1$, in contrast to the condition $n-k\geq dr$ required for the standard LRPC codes, where $d\geq n/(n-k)$. This underscores the superior decoding capability of the proposed BD-LRPC codes. As the code length $n$ approaches infinity, when $n/m\rightarrow 0$, it is shown that $u$ can be chosen as a certain constant, which indicates that the BD-LRPC codes with a code rate of $R$ can be, with a high probability, uniquely decodable with the decoding radius $\rho=r/n$ approaching the Singleton bound $1-R$ for $n \to \infty$; and when $b= n/m$ is a constant, the BD-LRPC codes can have unique decoding radius $\rho = 1-R-\epsilon$ for a small $\epsilon$, which can easily lead to $\rho>(1-R)/2$ with properly chosen parameters.Comment: Currently under revie