11,675 research outputs found
Geometrical relations between space time block code designs and complexity reduction
In this work, the geometric relation between space time block code design for
the coherent channel and its non-coherent counterpart is exploited to get an
analogue of the information theoretic inequality in
terms of diversity. It provides a lower bound on the performance of
non-coherent codes when used in coherent scenarios. This leads in turn to a
code design decomposition result splitting coherent code design into two
complexity reduced sub tasks. Moreover a geometrical criterion for high
performance space time code design is derived.Comment: final version, 11 pages, two-colum
Hyperuniformity Order Metric of Barlow Packings
The concept of hyperuniformity has been a useful tool in the study of
large-scale density fluctuations in systems ranging across the natural and
mathematical sciences. One can rank a large class of hyperuniform systems by
their ability to suppress long-range density fluctuations through the use of a
hyperuniformity order metric . We apply this order metric to the
Barlow packings, which are the infinitely degenerate densest packings of
identical rigid spheres that are distinguished by their stacking geometries and
include the commonly known fcc lattice and hcp crystal. The "stealthy stacking"
theorem implies that these packings are all stealthy hyperuniform, a strong
type of hyperuniformity which involves the suppression of scattering up to a
wavevector . We describe the geometry of three classes of Barlow packings,
two disordered classes and small-period packings. In addition, we compute a
lower bound on for all Barlow packings. We compute for the
aforementioned three classes of Barlow packings and find that to a very good
approximation, it is linear in the fraction of fcc-like clusters, taking values
between those of least-ordered hcp and most-ordered fcc. This implies that the
of all Barlow packings is primarily controlled by the local
cluster geometry. These results indicate the special nature of anisotropic
stacking disorder, which provides impetus for future research on the
development of anisotropic order metrics and hyperuniformity properties.Comment: 13 pages, 7 figure
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
Density of Spherically-Embedded Stiefel and Grassmann Codes
The density of a code is the fraction of the coding space covered by packing
balls centered around the codewords. This paper investigates the density of
codes in the complex Stiefel and Grassmann manifolds equipped with the chordal
distance. The choice of distance enables the treatment of the manifolds as
subspaces of Euclidean hyperspheres. In this geometry, the densest packings are
not necessarily equivalent to maximum-minimum-distance codes. Computing a
code's density follows from computing: i) the normalized volume of a metric
ball and ii) the kissing radius, the radius of the largest balls one can pack
around the codewords without overlapping. First, the normalized volume of a
metric ball is evaluated by asymptotic approximations. The volume of a small
ball can be well-approximated by the volume of a locally-equivalent tangential
ball. In order to properly normalize this approximation, the precise volumes of
the manifolds induced by their spherical embedding are computed. For larger
balls, a hyperspherical cap approximation is used, which is justified by a
volume comparison theorem showing that the normalized volume of a ball in the
Stiefel or Grassmann manifold is asymptotically equal to the normalized volume
of a ball in its embedding sphere as the dimension grows to infinity. Then,
bounds on the kissing radius are derived alongside corresponding bounds on the
density. Unlike spherical codes or codes in flat spaces, the kissing radius of
Grassmann or Stiefel codes cannot be exactly determined from its minimum
distance. It is nonetheless possible to derive bounds on density as functions
of the minimum distance. Stiefel and Grassmann codes have larger density than
their image spherical codes when dimensions tend to infinity. Finally, the
bounds on density lead to refinements of the standard Hamming bounds for
Stiefel and Grassmann codes.Comment: Two-column version (24 pages, 6 figures, 4 tables). To appear in IEEE
Transactions on Information Theor
Diversities and the Geometry of Hypergraphs
The embedding of finite metrics in has become a fundamental tool for
both combinatorial optimization and large-scale data analysis. One important
application is to network flow problems in which there is close relation
between max-flow min-cut theorems and the minimal distortion embeddings of
metrics into . Here we show that this theory can be generalized
considerably to encompass Steiner tree packing problems in both graphs and
hypergraphs. Instead of the theory of metrics and minimal distortion
embeddings, the parallel is the theory of diversities recently introduced by
Bryant and Tupper, and the corresponding theory of diversities and
embeddings which we develop here.Comment: 19 pages, no figures. This version: further small correction
Core congestion is inherent in hyperbolic networks
We investigate the impact the negative curvature has on the traffic
congestion in large-scale networks. We prove that every Gromov hyperbolic
network admits a core, thus answering in the positive a conjecture by
Jonckheere, Lou, Bonahon, and Baryshnikov, Internet Mathematics, 7 (2011) which
is based on the experimental observation by Narayan and Saniee, Physical Review
E, 84 (2011) that real-world networks with small hyperbolicity have a core
congestion. Namely, we prove that for every subset of vertices of a
-hyperbolic graph there exists a vertex of such that the
disk of radius centered at intercepts at least
one half of the total flow between all pairs of vertices of , where the flow
between two vertices is carried by geodesic (or quasi-geodesic)
-paths. A set intercepts the flow between two nodes and if
intersect every shortest path between and . Differently from what
was conjectured by Jonckheere et al., we show that is not (and cannot be)
the center of mass of but is a node close to the median of in the
so-called injective hull of . In case of non-uniform traffic between nodes
of (in this case, the unit flow exists only between certain pairs of nodes
of defined by a commodity graph ), we prove a primal-dual result showing
that for any the size of a -multi-core (i.e., the number
of disks of radius ) intercepting all pairs of is upper bounded by
the maximum number of pairwise -apart pairs of
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