97,300 research outputs found
Graph-Based Decoding in the Presence of ISI
We propose an approximation of maximum-likelihood detection in ISI channels
based on linear programming or message passing. We convert the detection
problem into a binary decoding problem, which can be easily combined with LDPC
decoding. We show that, for a certain class of channels and in the absence of
coding, the proposed technique provides the exact ML solution without an
exponential complexity in the size of channel memory, while for some other
channels, this method has a non-diminishing probability of failure as SNR
increases. Some analysis is provided for the error events of the proposed
technique under linear programming.Comment: 25 pages, 8 figures, Submitted to IEEE Transactions on Information
Theor
Approximate solutions of stochastic differential delay equations with Markovian switching
Our main aim is to develop the existence theory for the solutions to stochastic differential delay equations with Markovian switching (SDDEwMSs) and to establish the convergence theory for the Euler-Maruyama approximate solutions under the local Lipschitz condition. As an application, our results are used to discuss a stochastic delay population system with Markovian switching
Numerically optimized Markovian coupling and mixing in one-dimensional maps
Algorithms are introduced that produce optimal Markovian couplings for large finite-state-space discrete-time Markov chains with sparse transition matrices; these algorithms are applied to some toy models motivated by fluid-dynamical mixing problems at high Peclét number. An alternative definition of the time-scale of a mixing process is suggested. Finally, these algorithms are applied to the problem of coupling diffusion processes in an acute-angled triangle, and some of the simplifications that occur in continuum coupling problems are discussed
List and Unique Error-Erasure Decoding of Interleaved Gabidulin Codes with Interpolation Techniques
A new interpolation-based decoding principle for interleaved Gabidulin codes
is presented. The approach consists of two steps: First, a multi-variate
linearized polynomial is constructed which interpolates the coefficients of the
received word and second, the roots of this polynomial have to be found. Due to
the specific structure of the interpolation polynomial, both steps
(interpolation and root-finding) can be accomplished by solving a linear system
of equations. This decoding principle can be applied as a list decoding
algorithm (where the list size is not necessarily bounded polynomially) as well
as an efficient probabilistic unique decoding algorithm. For the unique
decoder, we show a connection to known unique decoding approaches and give an
upper bound on the failure probability. Finally, we generalize our approach to
incorporate not only errors, but also row and column erasures.Comment: accepted for Designs, Codes and Cryptography; presented in part at
WCC 2013, Bergen, Norwa
Robust Successive Compute-and-Forward over Multi-User Multi-Relay Networks
This paper develops efficient Compute-and-forward (CMF) schemes in multi-user
multi-relay networks. To solve the rank failure problem in CMF setups and to
achieve full diversity of the network, we introduce two novel CMF methods,
namely, extended CMF and successive CMF. The former, having low complexity, is
based on recovering multiple equations at relays. The latter utilizes
successive interference cancellation (SIC) to enhance the system performance
compared to the state-of-the-art schemes. Both methods can be utilized in a
network with different number of users, relays, and relay antennas, with
negligible feedback channels or signaling overhead. We derive new concise
formulations and explicit framework for the successive CMF method as well as an
approach to reduce its computational complexity. Our theoretical analysis and
computer simulations demonstrate the superior performance of our proposed CMF
methods over the conventional schemes. Furthermore, based on our simulation
results, the successive CMF method yields additional signal-to-noise ratio
gains and shows considerable robustness against channel estimation error,
compared to the extended CMF method.Comment: 44 pages, 10 figures, 1 table, accepted to be published in IEEE
Trans. on Vehicular Tec
Finding the Maximizers of the Information Divergence from an Exponential Family
This paper investigates maximizers of the information divergence from an
exponential family . It is shown that the -projection of a maximizer
to is a convex combination of and a probability measure with
disjoint support and the same value of the sufficient statistics . This
observation can be used to transform the original problem of maximizing
over the set of all probability measures into the maximization of
a function \Dbar over a convex subset of . The global maximizers of
both problems correspond to each other. Furthermore, finding all local
maximizers of \Dbar yields all local maximizers of .
This paper also proposes two algorithms to find the maximizers of \Dbar and
applies them to two examples, where the maximizers of were not
known before.Comment: 25 page
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