4,978 research outputs found
Soft Interference Cancellation for Random Coding in Massive Gaussian Multiple-Access
We utilize recent results on the exact block error probability of Gaussian
random codes in additive white Gaussian noise to analyze Gaussian random coding
for massive multiple-access at finite message length. Soft iterative
interference cancellation is found to closely approach the performance bounds
recently found in [1]. The existence of two fundamentally different regimes in
the trade-off between power and bandwidth efficiency reported in [2] is related
to much older results in [3] on power optimization by linear programming.
Furthermore, we tighten the achievability bounds of [1] in the low power regime
and show that orthogonal constellations are very close to the theoretical
limits for message lengths around 100 and above.Comment: Submitted to IEEE Transactions on Wireless Communications, 202
Replica Symmetry Breaking in Compressive Sensing
For noisy compressive sensing systems, the asymptotic distortion with respect
to an arbitrary distortion function is determined when a general class of
least-square based reconstruction schemes is employed. The sampling matrix is
considered to belong to a large ensemble of random matrices including i.i.d.
and projector matrices, and the source vector is assumed to be i.i.d. with a
desired distribution. We take a statistical mechanical approach by representing
the asymptotic distortion as a macroscopic parameter of a spin glass and
employing the replica method for the large-system analysis. In contrast to
earlier studies, we evaluate the general replica ansatz which includes the RS
ansatz as well as RSB. The generality of the solution enables us to study the
impact of symmetry breaking. Our numerical investigations depict that for the
reconstruction scheme with the "zero-norm" penalty function, the RS fails to
predict the asymptotic distortion for relatively large compression rates;
however, the one-step RSB ansatz gives a valid prediction of the performance
within a larger regime of compression rates.Comment: 7 pages, 3 figures, presented at ITA 201
Web Service Retrieval by Structured Models
Much of the information available on theWorldWideWeb cannot effectively be found by the help of search engines because the information is dynamically generated on a userâs request.This applies to online decision support services as well as Deep Web information. We present in this paper a retrieval system that uses a variant of structured modeling to describe such information services, and similarity of models for retrieval. The computational complexity of the similarity problem is discussed, and graph algorithms for retrieval on repositories of service descriptions are introduced. We show how bounds for combinatorial optimization problems can provide filter algorithms in a retrieval context. We report about an evaluation of the retrieval system in a classroom experiment and give computational results on a benchmark library.Economics ;
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