1,636 research outputs found
Efficient FFT-based Circulant Embedding Method and Subspace Algorithms for Wideband Single-carrier Equalization
In single-carrier transmission systems, wider bandwidth allows higher data rate by transmitting narrower pulses. For wireless applications, however, this means that the effective channel response is longer and the number of significant taps increases. This results in higher computational burden at the receiver. In this paper, we first review some well-known equalization methods and their shortcomings. Then we will propose the use of the circulant embedding method and the CG algorithm as efficient equalizers that are specifically well suited in dealing with long delay spread channels. These methods take advantage of the low computational complexity of the FFT algorithm, resulting in the same overall computational complexity of N log(N). Furthermore, when the CG algorithm is used correctly, it may perform better than the MMSE equalizer at a much lower cos
Constructing packings in Grassmannian manifolds via alternating projection
This paper describes a numerical method for finding good packings in
Grassmannian manifolds equipped with various metrics. This investigation also
encompasses packing in projective spaces. In each case, producing a good
packing is equivalent to constructing a matrix that has certain structural and
spectral properties. By alternately enforcing the structural condition and then
the spectral condition, it is often possible to reach a matrix that satisfies
both. One may then extract a packing from this matrix.
This approach is both powerful and versatile. In cases where experiments have
been performed, the alternating projection method yields packings that compete
with the best packings recorded. It also extends to problems that have not been
studied numerically. For example, it can be used to produce packings of
subspaces in real and complex Grassmannian spaces equipped with the
Fubini--Study distance; these packings are valuable in wireless communications.
One can prove that some of the novel configurations constructed by the
algorithm have packing diameters that are nearly optimal.Comment: 41 pages, 7 tables, 4 figure
Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors
While single measurement vector (SMV) models have been widely studied in
signal processing, there is a surging interest in addressing the multiple
measurement vectors (MMV) problem. In the MMV setting, more than one
measurement vector is available and the multiple signals to be recovered share
some commonalities such as a common support. Applications in which MMV is a
naturally occurring phenomenon include online streaming, medical imaging, and
video recovery. This work presents a stochastic iterative algorithm for the
support recovery of jointly sparse corrupted MMV. We present a variant of the
Sparse Randomized Kaczmarz algorithm for corrupted MMV and compare our proposed
method with an existing Kaczmarz type algorithm for MMV problems. We also
showcase the usefulness of our approach in the online (streaming) setting and
provide empirical evidence that suggests the robustness of the proposed method
to the distribution of the corruption and the number of corruptions occurring.Comment: 13 pages, 6 figure
Frame Permutation Quantization
Frame permutation quantization (FPQ) is a new vector quantization technique
using finite frames. In FPQ, a vector is encoded using a permutation source
code to quantize its frame expansion. This means that the encoding is a partial
ordering of the frame expansion coefficients. Compared to ordinary permutation
source coding, FPQ produces a greater number of possible quantization rates and
a higher maximum rate. Various representations for the partitions induced by
FPQ are presented, and reconstruction algorithms based on linear programming,
quadratic programming, and recursive orthogonal projection are derived.
Implementations of the linear and quadratic programming algorithms for uniform
and Gaussian sources show performance improvements over entropy-constrained
scalar quantization for certain combinations of vector dimension and coding
rate. Monte Carlo evaluation of the recursive algorithm shows that mean-squared
error (MSE) decays as 1/M^4 for an M-element frame, which is consistent with
previous results on optimal decay of MSE. Reconstruction using the canonical
dual frame is also studied, and several results relate properties of the
analysis frame to whether linear reconstruction techniques provide consistent
reconstructions.Comment: 29 pages, 5 figures; detailed added to proof of Theorem 4.3 and a few
minor correction
Analysis of Basis Pursuit Via Capacity Sets
Finding the sparsest solution for an under-determined linear system
of equations is of interest in many applications. This problem is
known to be NP-hard. Recent work studied conditions on the support size of
that allow its recovery using L1-minimization, via the Basis Pursuit
algorithm. These conditions are often relying on a scalar property of
called the mutual-coherence. In this work we introduce an alternative set of
features of an arbitrarily given , called the "capacity sets". We show how
those could be used to analyze the performance of the basis pursuit, leading to
improved bounds and predictions of performance. Both theoretical and numerical
methods are presented, all using the capacity values, and shown to lead to
improved assessments of the basis pursuit success in finding the sparest
solution of
MUBs inequivalence and affine planes
There are fairly large families of unitarily inequivalent complete sets of
N+1 mutually unbiased bases (MUBs) in C^N for various prime powers N. The
number of such sets is not bounded above by any polynomial as a function of N.
While it is standard that there is a superficial similarity between complete
sets of MUBs and finite affine planes, there is an intimate relationship
between these large families and affine planes. This note briefly summarizes
"old" results that do not appear to be well-known concerning known families of
complete sets of MUBs and their associated planes.Comment: This is the version of this paper appearing in J. Mathematical
Physics 53, 032204 (2012) except for format changes due to the journal's
style policie
Symmetric Informationally Complete Quantum Measurements
We consider the existence in arbitrary finite dimensions d of a POVM
comprised of d^2 rank-one operators all of whose operator inner products are
equal. Such a set is called a ``symmetric, informationally complete'' POVM
(SIC-POVM) and is equivalent to a set of d^2 equiangular lines in C^d.
SIC-POVMs are relevant for quantum state tomography, quantum cryptography, and
foundational issues in quantum mechanics. We construct SIC-POVMs in dimensions
two, three, and four. We further conjecture that a particular kind of
group-covariant SIC-POVM exists in arbitrary dimensions, providing numerical
results up to dimension 45 to bolster this claim.Comment: 8 page
The road to deterministic matrices with the restricted isometry property
The restricted isometry property (RIP) is a well-known matrix condition that
provides state-of-the-art reconstruction guarantees for compressed sensing.
While random matrices are known to satisfy this property with high probability,
deterministic constructions have found less success. In this paper, we consider
various techniques for demonstrating RIP deterministically, some popular and
some novel, and we evaluate their performance. In evaluating some techniques,
we apply random matrix theory and inadvertently find a simple alternative proof
that certain random matrices are RIP. Later, we propose a particular class of
matrices as candidates for being RIP, namely, equiangular tight frames (ETFs).
Using the known correspondence between real ETFs and strongly regular graphs,
we investigate certain combinatorial implications of a real ETF being RIP.
Specifically, we give probabilistic intuition for a new bound on the clique
number of Paley graphs of prime order, and we conjecture that the corresponding
ETFs are RIP in a manner similar to random matrices.Comment: 24 page
Measurements of Flavour Dependent Fragmentation Functions in Z^0 -> qq(bar) Events
Fragmentation functions for charged particles in Z -> qq(bar) events have
been measured for bottom (b), charm (c) and light (uds) quarks as well as for
all flavours together. The results are based on data recorded between 1990 and
1995 using the OPAL detector at LEP. Event samples with different flavour
compositions were formed using reconstructed D* mesons and secondary vertices.
The \xi_p = ln(1/x_E) distributions and the position of their maxima \xi_max
are also presented separately for uds, c and b quark events. The fragmentation
function for b quarks is significantly softer than for uds quarks.Comment: 29 pages, LaTeX, 5 eps figures (and colour figs) included, submitted
to Eur. Phys. J.
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