31,024 research outputs found
AND-OR tree analysis of distributed LT codes
In this contribution, we consider design of distributed LT codes, i.e., independent rateless encodings of multiple sources which communicate to a common relay, where relay is able to combine incoming packets from the sources and forwards them to receivers. We provide density evolution formulae for distributed LT codes, which allow us to formulate distributed LT code design problem and prove the equivalence of performance of distributed LT codes and LT codes with related parameters in the asymptotic regime. Furthermore, we demonstrate that allowing LT coding apparatus at both the sources and the relay may prove advantageous to coding only at the sources and coding only at the relay
Decentralised distributed fountain coding: asymptotic analysis and design
A class of generic decentralised distributed fountain coding schemes is introduced and the tools of analysis of the performance of such schemes are presented. It is demonstrated that the developed approach can be used to formulate a robust code design methodology in a number of instances. We show that two non-standard applications of fountain codes, fountain codes for distributed source coding and fountain codes for unequal error protection lie within this decentralised distributed fountain coding framework
Computing in Additive Networks with Bounded-Information Codes
This paper studies the theory of the additive wireless network model, in
which the received signal is abstracted as an addition of the transmitted
signals. Our central observation is that the crucial challenge for computing in
this model is not high contention, as assumed previously, but rather
guaranteeing a bounded amount of \emph{information} in each neighborhood per
round, a property that we show is achievable using a new random coding
technique.
Technically, we provide efficient algorithms for fundamental distributed
tasks in additive networks, such as solving various symmetry breaking problems,
approximating network parameters, and solving an \emph{asymmetry revealing}
problem such as computing a maximal input.
The key method used is a novel random coding technique that allows a node to
successfully decode the received information, as long as it does not contain
too many distinct values. We then design our algorithms to produce a limited
amount of information in each neighborhood in order to leverage our enriched
toolbox for computing in additive networks
Coded Slotted ALOHA with Varying Packet Loss Rate across Users
The recent research has established an analogy between successive
interference cancellation in slotted ALOHA framework and iterative
belief-propagation erasure-decoding, which has opened the possibility to
enhance random access protocols by utilizing theory and tools of
erasure-correcting codes. In this paper we present a generalization of the
and-or tree evaluation, adapted for the asymptotic analysis of the slotted
ALOHA-based random-access protocols, for the case when the contending users
experience different channel conditions, resulting in packet loss probability
that varies across users. We apply the analysis to the example of frameless
ALOHA, where users contend on a slot basis. We present results regarding the
optimal access probabilities and contention period lengths, such that the
throughput and probability of user resolution are maximized.Comment: 4 pages, submitted to GlobalSIP 201
Design and Analysis of Nonbinary LDPC Codes for Arbitrary Discrete-Memoryless Channels
We present an analysis, under iterative decoding, of coset LDPC codes over
GF(q), designed for use over arbitrary discrete-memoryless channels
(particularly nonbinary and asymmetric channels). We use a random-coset
analysis to produce an effect that is similar to output-symmetry with binary
channels. We show that the random selection of the nonzero elements of the
GF(q) parity-check matrix induces a permutation-invariance property on the
densities of the decoder messages, which simplifies their analysis and
approximation. We generalize several properties, including symmetry and
stability from the analysis of binary LDPC codes. We show that under a Gaussian
approximation, the entire q-1 dimensional distribution of the vector messages
is described by a single scalar parameter (like the distributions of binary
LDPC messages). We apply this property to develop EXIT charts for our codes. We
use appropriately designed signal constellations to obtain substantial shaping
gains. Simulation results indicate that our codes outperform multilevel codes
at short block lengths. We also present simulation results for the AWGN
channel, including results within 0.56 dB of the unconstrained Shannon limit
(i.e. not restricted to any signal constellation) at a spectral efficiency of 6
bits/s/Hz.Comment: To appear, IEEE Transactions on Information Theory, (submitted
October 2004, revised and accepted for publication, November 2005). The
material in this paper was presented in part at the 41st Allerton Conference
on Communications, Control and Computing, October 2003 and at the 2005 IEEE
International Symposium on Information Theor
Design and Analysis of LT Codes with Decreasing Ripple Size
In this paper we propose a new design of LT codes, which decreases the amount
of necessary overhead in comparison to existing designs. The design focuses on
a parameter of the LT decoding process called the ripple size. This parameter
was also a key element in the design proposed in the original work by Luby.
Specifically, Luby argued that an LT code should provide a constant ripple size
during decoding. In this work we show that the ripple size should decrease
during decoding, in order to reduce the necessary overhead. Initially we
motivate this claim by analytical results related to the redundancy within an
LT code. We then propose a new design procedure, which can provide any desired
achievable decreasing ripple size. The new design procedure is evaluated and
compared to the current state of the art through simulations. This reveals a
significant increase in performance with respect to both average overhead and
error probability at any fixed overhead
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