112 research outputs found
On the Geometry of Balls in the Grassmannian and List Decoding of Lifted Gabidulin Codes
The finite Grassmannian is defined as the set of all
-dimensional subspaces of the ambient space . 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
are sent through a network channel and, since errors may
occur during transmission, the received words can possible lie in
, where . In this paper, we study the balls in
with center that is not necessarily in
. 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 , 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
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 erasures and
deviations occur, then errors of rank can always be corrected provided that
, where 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 packets of length
over are transmitted, the complexity of the decoding algorithm is given
by operations in an extension field .Comment: Minor corrections; 42 pages, to be published at the IEEE Transactions
on Information Theor
Coding for Errors and Erasures in Random Network Coding
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 and the collection by the
receiver of a basis for a vector space . 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 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
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