112 research outputs found

    On the Geometry of Balls in the Grassmannian and List Decoding of Lifted Gabidulin Codes

    Get PDF
    The finite Grassmannian Gq(k,n)\mathcal{G}_{q}(k,n) is defined as the set of all kk-dimensional subspaces of the ambient space Fqn\mathbb{F}_{q}^{n}. Subsets of the finite Grassmannian are called constant dimension codes and have recently found an application in random network coding. In this setting codewords from Gq(k,n)\mathcal{G}_{q}(k,n) are sent through a network channel and, since errors may occur during transmission, the received words can possible lie in Gq(k′,n)\mathcal{G}_{q}(k',n), where k′≠kk'\neq k. In this paper, we study the balls in Gq(k,n)\mathcal{G}_{q}(k,n) with center that is not necessarily in Gq(k,n)\mathcal{G}_{q}(k,n). We describe the balls with respect to two different metrics, namely the subspace and the injection metric. Moreover, we use two different techniques for describing these balls, one is the Pl\"ucker embedding of Gq(k,n)\mathcal{G}_{q}(k,n), and the second one is a rational parametrization of the matrix representation of the codewords. With these results, we consider the problem of list decoding a certain family of constant dimension codes, called lifted Gabidulin codes. We describe a way of representing these codes by linear equations in either the matrix representation or a subset of the Pl\"ucker coordinates. The union of these equations and the equations which arise from the description of the ball of a given radius in the Grassmannian describe the list of codewords with distance less than or equal to the given radius from the received word.Comment: To be published in Designs, Codes and Cryptography (Springer

    A Rank-Metric Approach to Error Control in Random Network Coding

    Full text link
    The problem of error control in random linear network coding is addressed from a matrix perspective that is closely related to the subspace perspective of K\"otter and Kschischang. A large class of constant-dimension subspace codes is investigated. It is shown that codes in this class can be easily constructed from rank-metric codes, while preserving their distance properties. Moreover, it is shown that minimum distance decoding of such subspace codes can be reformulated as a generalized decoding problem for rank-metric codes where partial information about the error is available. This partial information may be in the form of erasures (knowledge of an error location but not its value) and deviations (knowledge of an error value but not its location). Taking erasures and deviations into account (when they occur) strictly increases the error correction capability of a code: if μ\mu erasures and δ\delta deviations occur, then errors of rank tt can always be corrected provided that 2t≤d−1+μ+δ2t \leq d - 1 + \mu + \delta, where dd is the minimum rank distance of the code. For Gabidulin codes, an important family of maximum rank distance codes, an efficient decoding algorithm is proposed that can properly exploit erasures and deviations. In a network coding application where nn packets of length MM over FqF_q are transmitted, the complexity of the decoding algorithm is given by O(dM)O(dM) operations in an extension field FqnF_{q^n}.Comment: Minor corrections; 42 pages, to be published at the IEEE Transactions on Information Theor

    Coding for Errors and Erasures in Random Network Coding

    Get PDF
    The problem of error-control in random linear network coding is considered. A ``noncoherent'' or ``channel oblivious'' model is assumed where neither transmitter nor receiver is assumed to have knowledge of the channel transfer characteristic. Motivated by the property that linear network coding is vector-space preserving, information transmission is modelled as the injection into the network of a basis for a vector space VV and the collection by the receiver of a basis for a vector space UU. A metric on the projective geometry associated with the packet space is introduced, and it is shown that a minimum distance decoder for this metric achieves correct decoding if the dimension of the space V∩UV \cap U is sufficiently large. If the dimension of each codeword is restricted to a fixed integer, the code forms a subset of a finite-field Grassmannian, or, equivalently, a subset of the vertices of the corresponding Grassmann graph. Sphere-packing and sphere-covering bounds as well as a generalization of the Singleton bound are provided for such codes. Finally, a Reed-Solomon-like code construction, related to Gabidulin's construction of maximum rank-distance codes, is described and a Sudan-style ``list-1'' minimum distance decoding algorithm is provided.Comment: This revised paper contains some minor changes and clarification
    • …
    corecore