Syndrome-Based Error-Erasure Decoding of Interleaved Linearized Reed-Solomon Codes

TL;DR

This paper introduces syndrome-based error-erasure decoding algorithms for interleaved Linearized Reed--Solomon codes, capable of correcting various error patterns with efficient complexity, and analyzes their probabilistic decoding performance.

Contribution

It presents novel unified syndrome-based decoders for interleaved LRS codes that handle errors and erasures jointly, with detailed complexity and probabilistic performance analysis.

Findings

Decoders can correct errors up to half the designed error-correction radius.

Probabilistic decoding exceeds the unique decoding radius with high probability.

Complexity of decoding algorithms is approximately O(sn^2) in most scenarios.

Abstract

Linearized Reed--Solomon (LRS) codes are sum-rank-metric codes that generalize both Reed--Solomon and Gabidulin codes. We study vertically and horizontally interleaved LRS (VILRS and HILRS) codes whose codewords consist of a fixed number of stacked or concatenated codewords of a chosen LRS code. Our unified presentation of results for horizontal and vertical interleaving is novel and simplifies the recognition of resembling patterns. This paper's main results are syndrome-based decoders for both VILRS and HILRS codes. We first consider an error-only setting and then present more general error-erasure decoders, which can handle full errors, row erasures, and column erasures simultaneously. Here, an erasure means that parts of the row space or the column space of the error are already known before decoding. We incorporate this knowledge directly into Berlekamp--Massey-like key equations and thus decode all error types jointly. The presented error-only and error-erasure decoders have an average complexity in $O(sn^2)$ and $\widetilde{O}(sn^2)$ in most scenarios, where $s$ is the interleaving order and $n$ denotes the length of the component code. Errors of sum-rank weight $\tau=t_{\mathcal{F}}+t_{\mathcal{R}}+t_{\mathcal{C}}$ consist of $t_{\mathcal{F}}$ full errors, $t_{\mathcal{R}}$ row erasures, and $t_{\mathcal{C}}$ column erasures. Their successful decoding can be guaranteed for $t_{\mathcal{F}}\leq\tfrac{1}{2}(n-k-t_{\mathcal{R}}-t_{\mathcal{C}})$, where $n$ and $k$ represent the length and the dimension of the component LRS code. Moreover, probabilistic decoding beyond the unique-decoding radius is possible with high probability when $t_{\mathcal{F}}\leq\tfrac{s}{s+1}(n-k-t_{\mathcal{R}}-t_{\mathcal{C}})$ holds for interleaving order $s$. We give an upper bound on the failure probability for probabilistic unique decoding and showcase its tightness via Monte Carlo simulations.