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0809.4101
|
On Gaussian MIMO BC-MAC Duality With Multiple Transmit Covariance
Constraints
|
cs.IT math.IT
|
Owing to the structure of the Gaussian multiple-input multiple-output (MIMO)
broadcast channel (BC), associated optimization problems such as capacity
region computation and beamforming optimization are typically non-convex, and
cannot be solved directly. One feasible approach to these problems is to
transform them into their dual multiple access channel (MAC) problems, which
are easier to deal with due to their convexity properties. The conventional
BC-MAC duality is established via BC-MAC signal transformation, and has been
successfully applied to solve beamforming optimization,
signal-to-interference-plus-noise ratio (SINR) balancing, and capacity region
computation. However, this conventional duality approach is applicable only to
the case, in which the base station (BS) of the BC is subject to a single sum
power constraint. An alternative approach is minimax duality, established by Yu
in the framework of Lagrange duality, which can be applied to solve the
per-antenna power constraint problem. This paper extends the conventional
BC-MAC duality to the general linear constraint case, and thereby establishes a
general BC-MAC duality. This new duality is applied to solve the capacity
computation and beamforming optimization for the MIMO and multiple-input
single-output (MISO) BC, respectively, with multiple linear constraints.
Moreover, the relationship between this new general BC-MAC duality and minimax
duality is also presented. It is shown that the general BC-MAC duality offers
more flexibility in solving BC optimization problems relative to minimax
duality. Numerical results are provided to illustrate the effectiveness of the
proposed algorithms.
|
0809.4149
|
Block Network Error Control Codes and Syndrome-based Complete Maximum
Likelihood Decoding
|
cs.IT math.IT
|
In this paper, network error control coding is studied for robust and
efficient multicast in a directed acyclic network with imperfect links. The
block network error control coding framework, BNEC, is presented and the
capability of the scheme to correct a mixture of symbol errors and packet
erasures and to detect symbol errors is studied. The idea of syndrome-based
decoding and error detection is introduced for BNEC, which removes the effect
of input data and hence decreases the complexity. Next, an efficient
three-stage syndrome-based BNEC decoding scheme for network error correction is
proposed, in which prior to finding the error values, the position of the edge
errors are identified based on the error spaces at the receivers. In addition
to bounded-distance decoding schemes for error correction up to the refined
Singleton bound, a complete decoding scheme for BNEC is also introduced.
Specifically, it is shown that using the proposed syndrome-based complete
decoding, a network error correcting code with redundancy order d for receiver
t, can correct d-1 random additive errors with a probability sufficiently close
to 1, if the field size is sufficiently large. Also, a complete maximum
likelihood decoding scheme for BNEC is proposed. As the probability of error in
different network edges is not equal in general, and given the equivalency of
certain edge errors within the network at a particular receiver, the number of
edge errors, assessed in the refined Singleton bound, is not a sufficient
statistic for ML decoding.
|
0809.4183
|
An Asymptotically Optimal RFID Authentication Protocol Against Relay
Attacks
|
cs.CR cs.IT math.IT
|
Relay attacks are a major concern for RFID systems: during an authentication
process an adversary transparently relays messages between a verifier and a
remote legitimate prover.
We present an authentication protocol suited for RFID systems. Our solution
is the first that prevents relay attacks without degrading the authentication
security level: it minimizes the probability that the verifier accepts a fake
proof of identity, whether or not a relay attack occurs.
|
0809.4296
|
State dependent computation using coupled recurrent networks
|
q-bio.NC cs.NE
|
Although conditional branching between possible behavioural states is a
hallmark of intelligent behavior, very little is known about the neuronal
mechanisms that support this processing. In a step toward solving this problem
we demonstrate by theoretical analysis and simulation how networks of richly
inter-connected neurons, such as those observed in the superficial layers of
the neocortex, can embed reliable robust finite state machines. We show how a
multi-stable neuronal network containing a number of states can be created very
simply, by coupling two recurrent networks whose synaptic weights have been
configured for soft winner-take-all (sWTA) performance. These two sWTAs have
simple, homogenous locally recurrent connectivity except for a small fraction
of recurrent cross-connections between them, which are used to embed the
required states. This coupling between the maps allows the network to continue
to express the current state even after the input that elicted that state is
withdrawn. In addition, a small number of 'transition neurons' implement the
necessary input-driven transitions between the embedded states. We provide
simple rules to systematically design and construct neuronal state machines of
this kind. The significance of our finding is that it offers a method whereby
the cortex could construct networks supporting a broad range of sophisticated
processing by applying only small specializations to the same generic neuronal
circuit.
|
0809.4316
|
A Layered Lattice Coding Scheme for a Class of Three User Gaussian
Interference Channels
|
cs.IT math.IT
|
The paper studies a class of three user Gaussian interference channels. A new
layered lattice coding scheme is introduced as a transmission strategy. The use
of lattice codes allows for an "alignment" of the interference observed at each
receiver. The layered lattice coding is shown to achieve more than one degree
of freedom for a class of interference channels and also achieves rates which
are better than the rates obtained using the Han-Kobayashi coding scheme.
|
0809.4325
|
On the Unicast Capacity of Stationary Multi-channel Multi-radio Wireless
Networks: Separability and Multi-channel Routing
|
cs.IT math.IT
|
The first result is on the separability of the unicast capacity of stationary
multi-channel multi-radio wireless networks, i.e., whether the capacity of such
a network is equal to the sum of the capacities of the corresponding
single-channel single-radio wireless networks. For both the Arbitrary Network
model and the Random Network model, given a channel assignment, the
separability property does not always hold. However, if the number of radio
interfaces at each node is equal to the number of channels, the separability
property holds. The second result is on the impact of multi-channel routing
(i.e., routing a bit through multiple channels as opposed to through a single
channel) on the network capacity. For both network models, the network
capacities conditioned on a channel assignment under the two routing schemes
are not always equal, but if again the number of radio interfaces at each node
is equal to the number of channels, the two routing schemes yield equal network
capacities.
|
0809.4484
|
Llull and Copeland Voting Computationally Resist Bribery and Control
|
cs.GT cs.CC cs.MA
|
The only systems previously known to be resistant to all the standard control
types were highly artificial election systems created by hybridization. We
study a parameterized version of Copeland voting, denoted by Copeland^\alpha,
where the parameter \alpha is a rational number between 0 and 1 that specifies
how ties are valued in the pairwise comparisons of candidates. We prove that
Copeland^{0.5}, the system commonly referred to as "Copeland voting," provides
full resistance to constructive control, and we prove the same for
Copeland^\alpha, for all rational \alpha, 0 < \alpha < 1. Copeland voting is
the first natural election system proven to have full resistance to
constructive control. We also prove that both Copeland^1 (Llull elections) and
Copeland^0 are resistant to all standard types of constructive control other
than one variant of addition of candidates. Moreover, we show that for each
rational \alpha, 0 \leq \alpha \leq 1, Copeland^\alpha voting is fully
resistant to bribery attacks, and we establish fixed-parameter tractability of
bounded-case control for Copeland^\alpha. We also study Copeland^\alpha
elections under more flexible models such as microbribery and extended control
and we integrate the potential irrationality of voter preferences into many of
our results.
|
0809.4501
|
Audio Classification from Time-Frequency Texture
|
cs.CV cs.SD
|
Time-frequency representations of audio signals often resemble texture
images. This paper derives a simple audio classification algorithm based on
treating sound spectrograms as texture images. The algorithm is inspired by an
earlier visual classification scheme particularly efficient at classifying
textures. While solely based on time-frequency texture features, the algorithm
achieves surprisingly good performance in musical instrument classification
experiments.
|
0809.4529
|
The Equivalence of Semidefinite Relaxation MIMO Detectors for
Higher-Order QAM
|
cs.IT math.IT math.OC
|
In multi-input-multi-output (MIMO) detection, semidefinite relaxation (SDR)
has been shown to be an efficient high-performance approach. Developed
initially for BPSK and QPSK, SDR has been found to be capable of providing
near-optimal performance (for those constellations). This has stimulated a
number of recent research endeavors that aim to apply SDR to the high-order QAM
cases. These independently developed SDRs are different in concept and
structure, and presently no serious analysis has been given to compare these
methods. This paper analyzes the relationship of three such SDR methods, namely
the polynomial-inspired SDR (PI-SDR) by Wiesel et al., the bound-constrained
SDR (BC-SDR) by Sidiropoulos and Luo, and the virtually-antipodal SDR (VA-SDR)
by Mao et al. The result that we have proven is somehow unexpected: the three
SDRs are equivalent. Simply speaking, we show that solving any one SDR is
equivalent to solving the other SDRs. This paper also discusses some
implications arising from the SDR equivalence, and provides simulation results
to verify our theoretical findings.
|
0809.4530
|
Mining Meaning from Wikipedia
|
cs.AI cs.CL cs.IR
|
Wikipedia is a goldmine of information; not just for its many readers, but
also for the growing community of researchers who recognize it as a resource of
exceptional scale and utility. It represents a vast investment of manual effort
and judgment: a huge, constantly evolving tapestry of concepts and relations
that is being applied to a host of tasks.
This article provides a comprehensive description of this work. It focuses on
research that extracts and makes use of the concepts, relations, facts and
descriptions found in Wikipedia, and organizes the work into four broad
categories: applying Wikipedia to natural language processing; using it to
facilitate information retrieval and information extraction; and as a resource
for ontology building. The article addresses how Wikipedia is being used as is,
how it is being improved and adapted, and how it is being combined with other
structures to create entirely new resources. We identify the research groups
and individuals involved, and how their work has developed in the last few
years. We provide a comprehensive list of the open-source software they have
produced.
|
0809.4577
|
A Generic Top-Down Dynamic-Programming Approach to Prefix-Free Coding
|
cs.DS cs.IT math.IT
|
Given a probability distribution over a set of n words to be transmitted, the
Huffman Coding problem is to find a minimal-cost prefix free code for
transmitting those words. The basic Huffman coding problem can be solved in O(n
log n) time but variations are more difficult. One of the standard techniques
for solving these variations utilizes a top-down dynamic programming approach.
In this paper we show that this approach is amenable to dynamic programming
speedup techniques, permitting a speedup of an order of magnitude for many
algorithms in the literature for such variations as mixed radix, reserved
length and one-ended coding. These speedups are immediate implications of a
general structural property that permits batching together the calculation of
many DP entries.
|
0809.4582
|
Achieving compositionality of the stable model semantics for Smodels
programs
|
cs.AI
|
In this paper, a Gaifman-Shapiro-style module architecture is tailored to the
case of Smodels programs under the stable model semantics. The composition of
Smodels program modules is suitably limited by module conditions which ensure
the compatibility of the module system with stable models. Hence the semantics
of an entire Smodels program depends directly on stable models assigned to its
modules. This result is formalized as a module theorem which truly strengthens
Lifschitz and Turner's splitting-set theorem for the class of Smodels programs.
To streamline generalizations in the future, the module theorem is first proved
for normal programs and then extended to cover Smodels programs using a
translation from the latter class of programs to the former class. Moreover,
the respective notion of module-level equivalence, namely modular equivalence,
is shown to be a proper congruence relation: it is preserved under
substitutions of modules that are modularly equivalent. Principles for program
decomposition are also addressed. The strongly connected components of the
respective dependency graph can be exploited in order to extract a module
structure when there is no explicit a priori knowledge about the modules of a
program. The paper includes a practical demonstration of tools that have been
developed for automated (de)composition of Smodels programs.
To appear in Theory and Practice of Logic Programming.
|
0809.4622
|
A computational approach to the covert and overt deployment of spatial
attention
|
cs.NE
|
Popular computational models of visual attention tend to neglect the
influence of saccadic eye movements whereas it has been shown that the primates
perform on average three of them per seconds and that the neural substrate for
the deployment of attention and the execution of an eye movement might
considerably overlap. Here we propose a computational model in which the
deployment of attention with or without a subsequent eye movement emerges from
local, distributed and numerical computations.
|
0809.4632
|
Surrogate Learning - An Approach for Semi-Supervised Classification
|
cs.LG
|
We consider the task of learning a classifier from the feature space
$\mathcal{X}$ to the set of classes $\mathcal{Y} = \{0, 1\}$, when the features
can be partitioned into class-conditionally independent feature sets
$\mathcal{X}_1$ and $\mathcal{X}_2$. We show the surprising fact that the
class-conditional independence can be used to represent the original learning
task in terms of 1) learning a classifier from $\mathcal{X}_2$ to
$\mathcal{X}_1$ and 2) learning the class-conditional distribution of the
feature set $\mathcal{X}_1$. This fact can be exploited for semi-supervised
learning because the former task can be accomplished purely from unlabeled
samples. We present experimental evaluation of the idea in two real world
applications.
|
0809.4668
|
Faceted Ranking of Egos in Collaborative Tagging Systems
|
cs.IR
|
Multimedia uploaded content is tagged and recommended by users of
collaborative systems, resulting in informal classifications also known as
folksonomies. Faceted web ranking has been proved a reasonable alternative to a
single ranking which does not take into account a personalized context. In this
paper we analyze the online computation of rankings of users associated to
facets made up of multiple tags. Possible applications are user reputation
evaluation (ego-ranking) and improvement of content quality in case of
retrieval. We propose a solution based on PageRank as centrality measure: (i) a
ranking for each tag is computed offline on the basis of the corresponding
tag-dependent subgraph; (ii) a faceted order is generated by merging rankings
corresponding to all the tags in the facet. The fundamental assumption,
validated by empirical observations, is that step (i) is scalable. We also
present algorithms for part (ii) having time complexity O(k), where k is the
number of tags in the facet, well suited to online computation.
|
0809.4743
|
The Imaginary Sliding Window As a New Data Structure for Adaptive
Algorithms
|
cs.IT cs.DS math.IT
|
The scheme of the sliding window is known in Information Theory, Computer
Science, the problem of predicting and in stastistics. Let a source with
unknown statistics generate some word $... x_{-1}x_{0}x_{1}x_{2}...$ in some
alphabet $A$. For every moment $t, t=... $ $-1, 0, 1, ...$, one stores the word
("window") $ x_{t-w} x_{t-w+1}... x_{t-1}$ where $w$,$w \geq 1$, is called
"window length". In the theory of universal coding, the code of the $x_{t}$
depends on source ststistics estimated by the window, in the problem of
predicting, each letter $x_{t}$ is predicted using information of the window,
etc. After that the letter $x_{t}$ is included in the window on the right,
while $x_{t-w}$ is removed from the window. It is the sliding window scheme.
This scheme has two merits: it allows one i) to estimate the source statistics
quite precisely and ii) to adapt the code in case of a change in the source'
statistics. However this scheme has a defect, namely, the necessity to store
the window (i.e. the word $x_{t-w}... x_{t-1})$ which needs a large memory size
for large $w$. A new scheme named "the Imaginary Sliding Window (ISW)" is
constructed. The gist of this scheme is that not the last element $x_{t-w}$ but
rather a random one is removed from the window. This allows one to retain both
merits of the sliding window as well as the possibility of not storing the
window and thus significantly decreasing the memory size.
|
0809.4784
|
A Computational Study on Emotions and Temperament in Multi-Agent Systems
|
cs.AI cs.MA cs.RO
|
Recent advances in neurosciences and psychology have provided evidence that
affective phenomena pervade intelligence at many levels, being inseparable from
the cognitionaction loop. Perception, attention, memory, learning,
decisionmaking, adaptation, communication and social interaction are some of
the aspects influenced by them. This work draws its inspirations from
neurobiology, psychophysics and sociology to approach the problem of building
autonomous robots capable of interacting with each other and building
strategies based on temperamental decision mechanism. Modelling emotions is a
relatively recent focus in artificial intelligence and cognitive modelling.
Such models can ideally inform our understanding of human behavior. We may see
the development of computational models of emotion as a core research focus
that will facilitate advances in the large array of computational systems that
model, interpret or influence human behavior. We propose a model based on a
scalable, flexible and modular approach to emotion which allows runtime
evaluation between emotional quality and performance. The results achieved
showed that the strategies based on temperamental decision mechanism strongly
influence the system performance and there are evident dependency between
emotional state of the agents and their temperamental type, as well as the
dependency between the team performance and the temperamental configuration of
the team members, and this enable us to conclude that the modular approach to
emotional programming based on temperamental theory is the good choice to
develop computational mind models for emotional behavioral Multi-Agent systems.
|
0809.4804
|
On the Secure Degrees of Freedom of Wireless X Networks
|
cs.IT math.IT
|
Previous work showed that the X network with M transmitters, N receivers has
MN/(M+N-1) degrees of freedom. In this work we study the degrees of freedom of
the X network with secrecy constraints, i.e. the X network where some/all
messages are confidential. We consider the $M \times N$ network where all
messages are secured and show that N(M-1)/(M+N-1) degrees of freedom can be
achieved. Secondly, we show that if messages from only M-1 transmitters are
confidential, then MN/(M+N-1) degrees of freedom can be achieved meaning that
there is no loss of degrees of freedom because of secrecy constraints. We also
consider the achievable secure degrees of freedom under a more conservative
secrecy constraint. We require that messages from any subset of transmitters
are secure even if other transmitters are compromised, i.e., messages from the
compromised transmitter are revealed to the unintended receivers. We also study
the achievable secure degrees of freedom of the K user Gaussian interference
channel under two different secrecy constraints where 1/2 secure degrees of
freedom per message can be achieved. The achievable scheme in all cases is
based on random binning combined with interference alignment.
|
0809.4807
|
Secure Wireless Communications via Cooperation
|
cs.IT math.IT
|
The feasibility of physical-layer-based security approaches for wireless
communications in the presence of one or more eavesdroppers is hampered by
channel conditions. In this paper, cooperation is investigated as an approach
to overcome this problem and improve the performance of secure communications.
In particular, a decode-and-forward (DF) based cooperative protocol is
considered, and the objective is to design the system for secrecy capacity
maximization or transmit power minimization. System design for the DF-based
cooperative protocol is first studied by assuming the availability of global
channel state information (CSI). For the case of one eavesdropper, an iterative
scheme is proposed to obtain the optimal solution for the problem of transmit
power minimization. For the case of multiple eavesdroppers, the problem of
secrecy capacity maximization or transmit power minimization is in general
intractable. Suboptimal system design is proposed by adding an additional
constraint, i.e., the complete nulling of signals at all eavesdroppers, which
yields simple closed-form solutions for the aforementioned two problems. Then,
the impact of imperfect CSI of eavesdroppers on system design is studied, in
which the ergodic secrecy capacity is of interest.
|
0809.4834
|
Relevance Feedback in Conceptual Image Retrieval: A User Evaluation
|
cs.IR
|
The Visual Object Information Retrieval (VOIR) system described in this paper
implements an image retrieval approach that combines two layers, the conceptual
and the visual layer. It uses terms from a textual thesaurus to represent the
conceptual information and also works with image regions, the visual
information. The terms are related with the image regions through a weighted
association enabling the execution of concept-level queries. VOIR uses
region-based relevance feedback to improve the quality of the results in each
query session and to discover new associations between text and image. This
paper describes a user-centred and task-oriented comparative evaluation of VOIR
which was undertaken considering three distinct versions of VOIR: a full-fledge
version; one supporting relevance feedback only at image level; and a third
version not supporting relevance feedback at all. The evaluation performed
showed the usefulness of region based relevance feedback in the context of VOIR
prototype.
|
0809.4882
|
Multi-Armed Bandits in Metric Spaces
|
cs.DS cs.LG
|
In a multi-armed bandit problem, an online algorithm chooses from a set of
strategies in a sequence of trials so as to maximize the total payoff of the
chosen strategies. While the performance of bandit algorithms with a small
finite strategy set is quite well understood, bandit problems with large
strategy sets are still a topic of very active investigation, motivated by
practical applications such as online auctions and web advertisement. The goal
of such research is to identify broad and natural classes of strategy sets and
payoff functions which enable the design of efficient solutions. In this work
we study a very general setting for the multi-armed bandit problem in which the
strategies form a metric space, and the payoff function satisfies a Lipschitz
condition with respect to the metric. We refer to this problem as the
"Lipschitz MAB problem". We present a complete solution for the multi-armed
problem in this setting. That is, for every metric space (L,X) we define an
isometry invariant which bounds from below the performance of Lipschitz MAB
algorithms for X, and we present an algorithm which comes arbitrarily close to
meeting this bound. Furthermore, our technique gives even better results for
benign payoff functions.
|
0809.4883
|
Thresholded Basis Pursuit: An LP Algorithm for Achieving Optimal Support
Recovery for Sparse and Approximately Sparse Signals from Noisy Random
Measurements
|
cs.IT cs.LG math.IT
|
In this paper we present a linear programming solution for sign pattern
recovery of a sparse signal from noisy random projections of the signal. We
consider two types of noise models, input noise, where noise enters before the
random projection; and output noise, where noise enters after the random
projection. Sign pattern recovery involves the estimation of sign pattern of a
sparse signal. Our idea is to pretend that no noise exists and solve the
noiseless $\ell_1$ problem, namely, $\min \|\beta\|_1 ~ s.t. ~ y=G \beta$ and
quantizing the resulting solution. We show that the quantized solution
perfectly reconstructs the sign pattern of a sufficiently sparse signal.
Specifically, we show that the sign pattern of an arbitrary k-sparse,
n-dimensional signal $x$ can be recovered with $SNR=\Omega(\log n)$ and
measurements scaling as $m= \Omega(k \log{n/k})$ for all sparsity levels $k$
satisfying $0< k \leq \alpha n$, where $\alpha$ is a sufficiently small
positive constant. Surprisingly, this bound matches the optimal
\emph{Max-Likelihood} performance bounds in terms of $SNR$, required number of
measurements, and admissible sparsity level in an order-wise sense. In contrast
to our results, previous results based on LASSO and Max-Correlation techniques
either assume significantly larger $SNR$, sublinear sparsity levels or
restrictive assumptions on signal sets. Our proof technique is based on noisy
perturbation of the noiseless $\ell_1$ problem, in that, we estimate the
maximum admissible noise level before sign pattern recovery fails.
|
0809.5005
|
Simulated annealing for weighted polygon packing
|
cs.CG cs.AI
|
In this paper we present a new algorithm for a layout optimization problem:
this concerns the placement of weighted polygons inside a circular container,
the two objectives being to minimize imbalance of mass and to minimize the
radius of the container. This problem carries real practical significance in
industrial applications (such as the design of satellites), as well as being of
significant theoretical interest. Previous work has dealt with circular or
rectangular objects, but here we deal with the more realistic case where
objects may be represented as polygons and the polygons are allowed to rotate.
We present a solution based on simulated annealing and first test it on
instances with known optima. Our results show that the algorithm obtains
container radii that are close to optimal. We also compare our method with
existing algorithms for the (special) rectangular case. Experimental results
show that our approach out-performs these methods in terms of solution quality.
|
0809.5008
|
Multi-Antenna Communication in Ad Hoc Networks: Achieving MIMO Gains
with SIMO Transmission
|
cs.IT math.IT
|
The benefit of multi-antenna receivers is investigated in wireless ad hoc
networks, and the main finding is that network throughput can be made to scale
linearly with the number of receive antennas nR even if each transmitting node
uses only a single antenna. This is in contrast to a large body of prior work
in single-user, multiuser, and ad hoc wireless networks that have shown linear
scaling is achievable when multiple receive and transmit antennas (i.e., MIMO
transmission) are employed, but that throughput increases logarithmically or
sublinearly with nR when only a single transmit antenna (i.e., SIMO
transmission) is used. The linear gain is achieved by using the receive degrees
of freedom to simultaneously suppress interference and increase the power of
the desired signal, and exploiting the subsequent performance benefit to
increase the density of simultaneous transmissions instead of the transmission
rate. This result is proven in the transmission capacity framework, which
presumes single-hop transmissions in the presence of randomly located
interferers, but it is also illustrated that the result holds under several
relaxations of the model, including imperfect channel knowledge, multihop
transmission, and regular networks (i.e., interferers are deterministically
located on grids).
|
0809.5009
|
Delay Constrained Scheduling over Fading Channels: Optimal Policies for
Monomial Energy-Cost Functions
|
cs.IT math.IT
|
A point-to-point discrete-time scheduling problem of transmitting $B$
information bits within $T$ hard delay deadline slots is considered assuming
that the underlying energy-bit cost function is a convex monomial. The
scheduling objective is to minimize the expected energy expenditure while
satisfying the deadline constraint based on information about the unserved
bits, channel state/statistics, and the remaining time slots to the deadline.
At each time slot, the scheduling decision is made without knowledge of future
channel state, and thus there is a tension between serving many bits when the
current channel is good versus leaving too many bits for the deadline. Under
the assumption that no other packet is scheduled concurrently and no outage is
allowed, we derive the optimal scheduling policy. Furthermore, we also
investigate the dual problem of maximizing the number of transmitted bits over
$T$ time slots when subject to an energy constraint.
|
0809.5022
|
Network coding meets TCP
|
cs.NI cs.IT math.IT
|
We propose a mechanism that incorporates network coding into TCP with only
minor changes to the protocol stack, thereby allowing incremental deployment.
In our scheme, the source transmits random linear combinations of packets
currently in the congestion window. At the heart of our scheme is a new
interpretation of ACKs - the sink acknowledges every degree of freedom (i.e., a
linear combination that reveals one unit of new information) even if it does
not reveal an original packet immediately. Such ACKs enable a TCP-like
sliding-window approach to network coding. Our scheme has the nice property
that packet losses are essentially masked from the congestion control
algorithm. Our algorithm therefore reacts to packet drops in a smooth manner,
resulting in a novel and effective approach for congestion control over
networks involving lossy links such as wireless links. Our experiments show
that our algorithm achieves higher throughput compared to TCP in the presence
of lossy wireless links. We also establish the soundness and fairness
properties of our algorithm.
|
0809.5023
|
Asymptotic stability region of slotted-Aloha
|
cs.IT math.IT
|
We analyze the stability of standard, buffered, slotted-Aloha systems.
Specifically, we consider a set of $N$ users, each equipped with an infinite
buffer. Packets arrive into user $i$'s buffer according to some stationary
ergodic Markovian process of intensity $\lambda_i$. At the beginning of each
slot, if user $i$ has packets in its buffer, it attempts to transmit a packet
with fixed probability $p_i$ over a shared resource / channel. The transmission
is successful only when no other user attempts to use the channel. The
stability of such systems has been open since their very first analysis in 1979
by Tsybakov and Mikhailov. In this paper, we propose an approximate stability
condition, that is provably exact when the number of users $N$ grows large. We
provide theoretical evidence and numerical experiments to explain why the
proposed approximate stability condition is extremely accurate even for systems
with a restricted number of users (even two or three). We finally extend the
results to the case of more efficient CSMA systems.
|
0809.5087
|
Hybrid Neural Network Architecture for On-Line Learning
|
cs.NE
|
Approaches to machine intelligence based on brain models have stressed the
use of neural networks for generalization. Here we propose the use of a hybrid
neural network architecture that uses two kind of neural networks
simultaneously: (i) a surface learning agent that quickly adapt to new modes of
operation; and, (ii) a deep learning agent that is very accurate within a
specific regime of operation. The two networks of the hybrid architecture
perform complementary functions that improve the overall performance. The
performance of the hybrid architecture has been compared with that of
back-propagation perceptrons and the CC and FC networks for chaotic time-series
prediction, the CATS benchmark test, and smooth function approximation. It has
been shown that the hybrid architecture provides a superior performance based
on the RMS error criterion.
|
0809.5096
|
Diversity Analysis of Bit-Interleaved Coded Multiple Beamforming
|
cs.IT math.IT
|
In this paper, diversity analysis of bit-interleaved coded multiple
beamforming (BICMB) is extended to the case of general spatial interleavers,
removing a condition on their previously known design criteria and quantifying
the resulting diversity order. The diversity order is determined by a parameter
Qmax which is inherited from the convolutional code and the spatial
de-multiplexer used in BICMB. We introduce a method to find this parameter by
employing a transfer function approach as in finding the weight spectrum of a
convolutional code. By using this method, several Qmax values are shown and
verified to be identical with the results from a computer search. The diversity
analysis and the method to find the parameter are supported by simulation
results. By using the Singleton bound, we also show that Qmax is lower bounded
by the product of the number of streams and the code rate of an encoder. The
design rule of the spatial de-multiplexer for a given convolutional code is
proposed to meet the condition on the maximum achievable diversity order.
|
0809.5153
|
On a new multivariate sampling paradigm and a polyspline Shannon
function
|
math.NA cs.IT math.IT
|
In the monograph Kounchev, O. I., Multivariate Polysplines. Applications to
Numerical and Wavelet Analysis, Academic Press, San Diego-London, 2001, and in
the paper Kounchev O., Render, H., Cardinal interpolation with polysplines on
annuli, Journal of Approximation Theory 137 (2005) 89--107, we have introduced
and studied a new paradigm for cardinal interpolation which is related to the
theory of multivariate polysplines. In the present paper we show that this is
related to a new sampling paradigm in the multivariate case, whereas we obtain
a Shannon type function $S(x) $ and the following Shannon type formula:
$f(r\theta) =\sum_{j=-\infty}^{\infty}\int_{\QTR{Bbb}{S}^{n-1}}S(e^{-j}r\theta
) f(e^{j}\theta) d\theta .$ This formula relies upon infinitely many Shannon
type formulas for the exponential splines arising from the radial part of the
polyharmonic operator $\Delta ^{p}$ for fixed $p\geq 1$. Acknowledgement. The
first and the second author have been partially supported by the Institutes
partnership project with the Alexander von Humboldt Foundation. The first has
been partially sponsored by the Greek-Bulgarian bilateral project BGr-17, and
the second author by Grant MTM2006-13000-C03-03 of the D.G.I. of Spain.
|
0809.5182
|
Perturbation-based Distributed Beamforming for Wireless Relay Networks
|
cs.IT math.IT
|
This paper deals with distributed beamforming techniques for wireless
networks with half-duplex amplify-and-forward relays. Existing schemes optimize
the beamforming weights based on the assumption that channel state information
(CSI) is available at the relays. We propose to use adaptive beamforming based
on deterministic perturbations and limited feedback (1-bit) from the
destination to the relays in order to avoid CSI at the relays. Two scalable
perturbation schemes are considered and practical implementation aspects are
addressed. Simulation results confirm that the proposed techniques closely
approach optimum performance and have satisfactory tracking properties in
time-varying environments.
|
0809.5191
|
A Coded Bit-Loading Linear Precoded Discrete Multitone Solution for
Power Line Communication
|
cs.IT math.IT
|
Linear precoded discrete multitone modulation (LP-DMT) system has been
already proved advantageous with adaptive resource allocation algorithm in a
power line communication (PLC) context. In this paper, we investigate the bit
and energy allocation algorithm of an adaptive LP-DMT system taking into
account the channel coding scheme. A coded adaptive LP-DMT system is presented
in the PLC context with a loading algorithm which ccommodates the channel
coding gains in bit and energy calculations. The performance of a concatenated
channel coding scheme, consisting of an inner Wei's 4-dimensional 16-states
trellis code and an outer Reed-Solomon code, in combination with the roposed
algorithm is analyzed. Simulation results are presented for a fixed target bit
error rate in a multicarrier scenario under power spectral density constraint.
Using a multipath model of PLC channel, it is shown that the proposed coded
adaptive LP-DMT system performs better than classical coded discrete multitone.
|
0809.5204
|
A Distributed MAC Protocol for Cooperation in Random Access Networks
|
cs.IT math.IT
|
WLAN is one of the most successful applications of wireless communications in
daily life because of low cost and ease of deployment. The enabling technique
for this success is the use of random access schemes for the wireless channel.
Random access requires minimal coordination between the nodes, which
considerably reduces the cost of the infrastructure. Recently, cooperative
communication in wireless networks has been of increasing interest because it
promises higher rates and reliability. An additional MAC overhead is necessary
to coordinate the nodes to allow cooperation and this overhead can possibly
cancel out the cooperative benefits. In this work, a completely distributed
protocol is proposed that allows nodes in the network to cooperate via Two-Hop
and Decode-and-Forward for transmitting their data to a common gateway node. It
is shown that high throughput gains are obtained in terms of the individual
throughput that can be guaranteed to any node in the network. These results are
validated by Monte Carlo simulations.
|
0809.5212
|
Secrecy Capacity over Correlated Ergodic Fading Channel
|
cs.IT math.IT
|
We investigate the secrecy capacity of an ergodic fading wiretap channel in
which the main channel is correlated with the eavesdropper channel. In this
study, the full Channel State Information (CSI) is assumed, and thus the
transmitter knows the channel gains of the legitimate receiver and the
eavesdropper. By analyzing the resulting secrecy capacity we quantify the loss
of the secrecy capacity due to the correlation. In addition, we study the
asymptotic behavior of the secrecy capacity as Signal-to-Noise Ratio (SNR)
tends to infinity. The capacity of an ordinary fading channel logarithmically
increases with SNR. On the contrary, the secrecy capacity converges into a
limit which can be an upper bound on the secrecy capacity over the fading
wiretap channel. We find a closed form of the upper bound for the correlated
Rayleigh wiretap channel which also includes the independent case as a special
one. Our work shows that the upper bound is determined by only two channel
parameters; the correlation coefficient and the ratio of the main to the
eavesdropper channel gains that will be called PCC and CGR respectively. The
analysis of the upper bound tells how the two channel parameters affect the
secrecy capacity and leads to the conclusion that the excessively large signal
power does not provide any advantage in the secrecy capacity, and the loss due
to the correlation is especially serious in low CGR regime.
|
0809.5217
|
Linear Universal Decoding for Compound Channels: a Local to Global
Geometric Approach
|
cs.IT math.IT math.PR
|
Over discrete memoryless channels (DMC), linear decoders (maximizing additive
metrics) afford several nice properties. In particular, if suitable encoders
are employed, the use of decoding algorithm with manageable complexities is
permitted. Maximum likelihood is an example of linear decoder. For a compound
DMC, decoders that perform well without the channel's knowledge are required in
order to achieve capacity. Several such decoders have been studied in the
literature. However, there is no such known decoder which is linear. Hence, the
problem of finding linear decoders achieving capacity for compound DMC is
addressed, and it is shown that under minor concessions, such decoders exist
and can be constructed. This paper also develops a "local geometric analysis",
which allows in particular, to solve the above problem. By considering very
noisy channels, the original problem is reduced, in the limit, to an inner
product space problem, for which insightful solutions can be found. The local
setting can then provide counterexamples to disproof claims, but also, it is
shown how in this problem, results proven locally can be "lifted" to results
proven globally.
|
0809.5275
|
Coded Adaptive Linear Precoded Discrete Multitone Over PLC Channel
|
cs.IT math.IT
|
Discrete multitone modulation (DMT) systems exploit the capabilities of
orthogonal subcarriers to cope efficiently with narrowband interference, high
frequency attenuations and multipath fadings with the help of simple
equalization filters. Adaptive linear precoded discrete multitone (LP-DMT)
system is based on classical DMT, combined with a linear precoding component.
In this paper, we investigate the bit and energy allocation algorithm of an
adaptive LP-DMT system taking into account the channel coding scheme. A coded
adaptive LPDMT system is presented in the power line communication (PLC)
context with a loading algorithm which accommodates the channel coding gains in
bit and energy calculations. The performance of a concatenated channel coding
scheme, consisting of an inner Wei's 4-dimensional 16-states trellis code and
an outer Reed-Solomon code, in combination with the proposed algorithm is
analyzed. Theoretical coding gains are derived and simulation results are
presented for a fixed target bit error rate in a multicarrier scenario under
power spectral density constraint. Using a multipath model of PLC channel, it
is shown that the proposed coded adaptive LP-DMT system performs better than
coded DMT and can achieve higher throughput for PLC applications.
|
0810.0068
|
On the Index Coding Problem and its Relation to Network Coding and
Matroid Theory
|
cs.IT math.IT
|
The \emph{index coding} problem has recently attracted a significant
attention from the research community due to its theoretical significance and
applications in wireless ad-hoc networks. An instance of the index coding
problem includes a sender that holds a set of information messages
$X=\{x_1,...,x_k\}$ and a set of receivers $R$. Each receiver $\rho=(x,H)\in R$
needs to obtain a message $x\in X$ and has prior \emph{side information}
comprising a subset $H$ of $X$. The sender uses a noiseless communication
channel to broadcast encoding of messages in $X$ to all clients. The objective
is to find an encoding scheme that minimizes the number of transmissions
required to satisfy the receivers' demands with \emph{zero error}.
In this paper, we analyze the relation between the index coding problem, the
more general network coding problem and the problem of finding a linear
representation of a matroid. In particular, we show that any instance of the
network coding and matroid representation problems can be efficiently reduced
to an instance of the index coding problem. Our reduction implies that many
important properties of the network coding and matroid representation problems
carry over to the index coding problem. Specifically, we show that \emph{vector
linear codes} outperform scalar linear codes and that vector linear codes are
insufficient for achieving the optimum number of transmissions.
|
0810.0139
|
Determining the Unithood of Word Sequences using a Probabilistic
Approach
|
cs.AI
|
Most research related to unithood were conducted as part of a larger effort
for the determination of termhood. Consequently, novelties are rare in this
small sub-field of term extraction. In addition, existing work were mostly
empirically motivated and derived. We propose a new probabilistically-derived
measure, independent of any influences of termhood, that provides dedicated
measures to gather linguistic evidence from parsed text and statistical
evidence from Google search engine for the measurement of unithood. Our
comparative study using 1,825 test cases against an existing
empirically-derived function revealed an improvement in terms of precision,
recall and accuracy.
|
0810.0154
|
Optimization of sequences in CDMA systems: a statistical-mechanics
approach
|
cs.IT math.IT
|
Statistical mechanics approach is useful not only in analyzing macroscopic
system performance of wireless communication systems, but also in discussing
design problems of wireless communication systems. In this paper, we discuss a
design problem of spreading sequences in code-division multiple-access (CDMA)
systems, as an example demonstrating the usefulness of statistical mechanics
approach. We analyze, via replica method, the average mutual information
between inputs and outputs of a randomly-spread CDMA channel, and discuss the
optimization problem with the average mutual information as a measure of
optimization. It has been shown that the average mutual information is
maximized by orthogonally-invariant random Welch bound equality (WBE) spreading
sequences.
|
0810.0156
|
Determining the Unithood of Word Sequences using Mutual Information and
Independence Measure
|
cs.AI
|
Most works related to unithood were conducted as part of a larger effort for
the determination of termhood. Consequently, the number of independent research
that study the notion of unithood and produce dedicated techniques for
measuring unithood is extremely small. We propose a new approach, independent
of any influences of termhood, that provides dedicated measures to gather
linguistic evidence from parsed text and statistical evidence from Google
search engine for the measurement of unithood. Our evaluations revealed a
precision and recall of 98.68% and 91.82% respectively with an accuracy at
95.42% in measuring the unithood of 1005 test cases.
|
0810.0200
|
Distribution of complexities in the Vai script
|
cs.CL
|
In the paper, we analyze the distribution of complexities in the Vai script,
an indigenous syllabic writing system from Liberia. It is found that the
uniformity hypothesis for complexities fails for this script. The models using
Poisson distribution for the number of components and hyper-Poisson
distribution for connections provide good fits in the case of the Vai script.
|
0810.0326
|
Collision Resolution by Exploiting Symbol Misalignment
|
cs.NI cs.IT math.IT
|
This paper presents CRESM, a novel collision resolution method for decoding
collided packets in random-access wireless networks. In a collision,
overlapping signals from several sources are received simultaneously at a
receiver. CRESM exploits symbol misalignment among the overlapping signals to
recover the individual packets. CRESM can be adopted in 802.11 networks without
modification of the transmitter design; only a simple DSP technique is needed
at the receiver to decode the overlapping signals. Our simulations indicate
that CRESM has better BER performance than the simplistic Successive
Interference Cancellation (SIC) technique that treats interference as noise,
for almost all SNR regimes. The implication of CRESM for random-access
networking is significant: in general, using CRESM to resolve collisions of up
to n packets, network throughput can be boosted by more than n times if the
transmitters are allowed to transmit more aggressively in the MAC protocol.
|
0810.0332
|
Enhanced Integrated Scoring for Cleaning Dirty Texts
|
cs.AI
|
An increasing number of approaches for ontology engineering from text are
gearing towards the use of online sources such as company intranet and the
World Wide Web. Despite such rise, not much work can be found in aspects of
preprocessing and cleaning dirty texts from online sources. This paper presents
an enhancement of an Integrated Scoring for Spelling error correction,
Abbreviation expansion and Case restoration (ISSAC). ISSAC is implemented as
part of a text preprocessing phase in an ontology engineering system. New
evaluations performed on the enhanced ISSAC using 700 chat records reveal an
improved accuracy of 98% as compared to 96.5% and 71% based on the use of only
basic ISSAC and of Aspell, respectively.
|
0810.0503
|
On the Capacity of One-sided Two user Gaussian Fading Broadcast Channels
|
cs.IT math.IT
|
In this paper, we investigate upper and lower bounds on the capacity of
two-user fading broadcast channels where one of the users has a constant
(non-fading) channel. We use the Costa entropy power inequality (EPI) along
with an optimization framework to derive upper bounds on the sum-capacity and
superposition coding to obtain lower bounds on the sum-rate for this channel.
For this fading broadcast channel where one channel is constant, we find that
the upper and lower bounds meet under special cases, and in general, we show
that the achievable sum-rate comes within a constant of the outer bound.
|
0810.0532
|
Three New Complexity Results for Resource Allocation Problems
|
cs.MA cs.AI cs.CC cs.GT
|
We prove the following results for task allocation of indivisible resources:
- The problem of finding a leximin-maximal resource allocation is in P if the
agents have max-utility functions and atomic demands.
- Deciding whether a resource allocation is Pareto-optimal is coNP-complete
for agents with (1-)additive utility functions.
- Deciding whether there exists a Pareto-optimal and envy-free resource
allocation is Sigma_2^p-complete for agents with (1-)additive utility
functions.
|
0810.0567
|
Reed-Solomon Subcodes with Nontrivial Traces: Distance Properties and
Soft-Decision Decoding
|
cs.IT math.IT
|
Reed-Solomon (RS) codes over GF$(2^m)$ have traditionally been the most
popular non-binary codes in almost all practical applications. The distance
properties of RS codes result in excellent performance under hard-decision
bounded-distance decoding. However, efficient and implementable soft decoding
for high-rate (about 0.9) RS codes over large fields (GF(256), say) continues
to remain a subject of research with a promise of further coding gains. In this
work, our objective is to propose and investigate $2^m$-ary codes with
non-trivial binary trace codes as an alternative to RS codes. We derive bounds
on the rate of a $2^m$-ary code with a non-trivial binary trace code. Then we
construct certain subcodes of RS codes over GF($2^m$) that have a non-trivial
binary trace with distances and rates meeting the derived bounds. The
properties of these subcodes are studied and low-complexity hard-decision and
soft-decision decoders are proposed. The decoders are analyzed, and their
performance is compared with that of comparable RS codes. Our results suggest
that these subcodes of RS codes could be viable alternatives for RS codes in
applications.
|
0810.0747
|
A New Upper Bound on the Capacity of a Class of Primitive Relay Channels
|
cs.IT cs.AI math.IT
|
We obtain a new upper bound on the capacity of a class of discrete memoryless
relay channels. For this class of relay channels, the relay observes an i.i.d.
sequence $T$, which is independent of the channel input $X$. The channel is
described by a set of probability transition functions $p(y|x,t)$ for all
$(x,t,y)\in \mathcal{X}\times \mathcal{T}\times \mathcal{Y}$. Furthermore, a
noiseless link of finite capacity $R_{0}$ exists from the relay to the
receiver. Although the capacity for these channels is not known in general, the
capacity of a subclass of these channels, namely when $T=g(X,Y)$, for some
deterministic function $g$, was obtained in [1] and it was shown to be equal to
the cut-set bound. Another instance where the capacity was obtained was in [2],
where the channel output $Y$ can be written as $Y=X\oplus Z$, where $\oplus$
denotes modulo-$m$ addition, $Z$ is independent of $X$,
$|\mathcal{X}|=|\mathcal{Y}|=m$, and $T$ is some stochastic function of $Z$.
The compress-and-forward (CAF) achievability scheme [3] was shown to be
capacity achieving in both cases.
Using our upper bound we recover the capacity results of [1] and [2]. We also
obtain the capacity of a class of channels which does not fall into either of
the classes studied in [1] and [2]. For this class of channels, CAF scheme is
shown to be optimal but capacity is strictly less than the cut-set bound for
certain values of $R_{0}$. We also evaluate our outer bound for a particular
relay channel with binary multiplicative states and binary additive noise for
which the channel is given as $Y=TX+N$. We show that our upper bound is
strictly better than the cut-set upper bound for certain values of $R_{0}$ but
it lies strictly above the rates yielded by the CAF achievability scheme.
|
0810.0763
|
Errorless Codes for Over-loaded CDMA with Active User Detection
|
cs.IT math.IT
|
In this paper we introduce a new class of codes for over-loaded synchronous
wireless CDMA systems which increases the number of users for a fixed number of
chips without introducing any errors. In addition these codes support active
user detection. We derive an upper bound on the number of users with a fixed
spreading factor. Also we propose an ML decoder for a subclass of these codes
that is computationally implementable. Although for our simulations we consider
a scenario that is worse than what occurs in practice, simulation results
indicate that this coding/decoding scheme is robust against additive noise. As
an example, for 64 chips and 88 users we propose a coding/decoding scheme that
can obtain an arbitrary small probability of error which is computationally
feasible and can detect active users. Furthermore, we prove that for this to be
possible the number of users cannot be beyond 230.
|
0810.0764
|
A New Method for Constructing Large Size WBE Codes with Low Complexity
ML Decoder
|
cs.IT math.IT
|
In this paper we wish to introduce a method to reconstruct large size Welch
Bound Equality (WBE) codes from small size WBE codes. The advantage of these
codes is that the implementation of ML decoder for the large size codes is
reduced to implementation of ML decoder for the core codes. This leads to a
drastic reduction of the computational cost of ML decoder. Our method can also
be used for constructing large Binary WBE (BWBE) codes from smaller ones.
Additionally, we explain that although WBE codes are maximizing the sum channel
capacity when the inputs are real valued, they are not necessarily appropriate
when the input alphabet is binary. The discussion shows that when the input
alphabet is binary, the Total Squared Correlation (TSC) of codes is not a
proper figure of merit.
|
0810.0785
|
Novel Bounds on the Capacity of the Binary Deletion Channel
|
cs.IT math.IT
|
We present novel bounds on the capacity of the independent and identically
distributed binary deletion channel. Four upper bounds are obtained by
providing the transmitter and the receiver with genie-aided information on
suitably-defined random processes. Since some of the proposed bounds involve
infinite series, we also introduce provable inequalities that lead to more
manageable results. For most values of the deletion probability, these bounds
improve the existing ones and significantly narrow the gap with the available
lower bounds. Exploiting the same auxiliary processes, we also derive, as a
by-product, a couple of very simple lower bounds on the channel capacity,
which, for low values of the deletion probability, are almost as good as the
best existing lower bounds.
|
0810.0830
|
Stiffness Analysis Of Multi-Chain Parallel Robotic Systems
|
cs.RO physics.class-ph
|
The paper presents a new stiffness modelling method for multi-chain parallel
robotic manipulators with flexible links and compliant actuating joints. In
contrast to other works, the method involves a FEA-based link stiffness
evaluation and employs a new solution strategy of the kinetostatic equations,
which allows computing the stiffness matrix for singular postures and to take
into account influence of the internal forces. The advantages of the developed
technique are confirmed by application examples, which deal with stiffness
analysis of the Orthoglide manipulator.
|
0810.0852
|
Evaluation of Authors and Journals
|
math.HO cs.IR physics.soc-ph
|
A method is presented for evaluating authors on the basis of citations. It
assigns to each author a citation score which depends upon the number of times
he is cited, and upon the scores of the citers. The scores are found to be the
components of an eigenvector of a normalized citation matrix. The same method
can be applied to citation of journals by other journals, to evaluating teams
in a league [1], etc.
|
0810.0870
|
Cognitive Radio with Partial Channel State Information at the
Transmitter
|
cs.IT math.IT
|
In this paper, we present the cognitive radio system design with partial
channel state information known at the transmitter (CSIT).We replace the dirty
paper coding (DPC) used in the cognitive radio with full CSIT by the linear
assignment Gel'fand-Pinsker coding (LA-GPC), which can utilize the limited
knowledge of the channel more efficiently. Based on the achievable rate derived
from the LA-GPC, two optimization problems under the fast and slow fading
channels are formulated. We derive semianalytical solutions to find the
relaying ratios and precoding coefficients. The critical observation is that
the complex rate functions in these problems are closely related to ratios of
quadratic form. Simulation results show that the proposed semi-analytical
solutions perform close to the optimal solutions found by brute-force search,
and outperform the systems based on naive DPC. Asymptotic analysis also shows
that these solutions converge to the optimal ones solved with full CSIT when
the K-factor of Rician channel approaches infinity. Moreover, a new coding
scheme is proposed to implement the LA-GPC in practice. Simulation results show
that the proposed practical coding scheme can efficiently reach the theoretical
rate performance.
|
0810.0877
|
Bias-Variance Techniques for Monte Carlo Optimization: Cross-validation
for the CE Method
|
cs.NA cs.LG
|
In this paper, we examine the CE method in the broad context of Monte Carlo
Optimization (MCO) and Parametric Learning (PL), a type of machine learning. A
well-known overarching principle used to improve the performance of many PL
algorithms is the bias-variance tradeoff. This tradeoff has been used to
improve PL algorithms ranging from Monte Carlo estimation of integrals, to
linear estimation, to general statistical estimation. Moreover, as described
by, MCO is very closely related to PL. Owing to this similarity, the
bias-variance tradeoff affects MCO performance, just as it does PL performance.
In this article, we exploit the bias-variance tradeoff to enhance the
performance of MCO algorithms. We use the technique of cross-validation, a
technique based on the bias-variance tradeoff, to significantly improve the
performance of the Cross Entropy (CE) method, which is an MCO algorithm. In
previous work we have confirmed that other PL techniques improve the perfomance
of other MCO algorithms. We conclude that the many techniques pioneered in PL
could be investigated as ways to improve MCO algorithms in general, and the CE
method in particular.
|
0810.0882
|
Asymptotic Eigenvalue Moments of Wishart-Type Random Matrix Without
Ergodicity in One Channel Realization
|
cs.IT math.IT
|
Consider a random matrix whose variance profile is random. This random matrix
is ergodic in one channel realization if, for each column and row, the
empirical distribution of the squared magnitudes of elements therein converges
to a nonrandom distribution. In this paper, noncrossing partition theory is
employed to derive expressions for several asymptotic eigenvalue moments (AEM)
related quantities of a large Wishart-type random matrix $\bb H\bb H^\dag$ when
$\bb H$ has a random variance profile and is nonergodic in one channel
realization. It is known the empirical eigenvalue moments of $\bb H\bb H^\dag$
are dependent (or independent) on realizations of the variance profile of $\bb
H$ when $\bb H$ is nonergodic (or ergodic) in one channel realization. For
nonergodic $\bb H$, the AEM can be obtained by i) deriving the expression of
AEM in terms of the variance profile of $\bb H$, and then ii) averaging the
derived quantity over the ensemble of variance profiles. Since the AEM are
independent of the variance profile if $\bb H$ is ergodic, the expression
obtained in i) can also serve as the AEM formula for ergodic $\bb H$ when any
realization of variance profile is available.
|
0810.0883
|
Asymptotic Performance of Linear Receivers in MIMO Fading Channels
|
cs.IT math.IT
|
Linear receivers are an attractive low-complexity alternative to optimal
processing for multi-antenna MIMO communications. In this paper we characterize
the information-theoretic performance of MIMO linear receivers in two different
asymptotic regimes. For fixed number of antennas, we investigate the limit of
error probability in the high-SNR regime in terms of the Diversity-Multiplexing
Tradeoff (DMT). Following this, we characterize the error probability for fixed
SNR in the regime of large (but finite) number of antennas.
As far as the DMT is concerned, we report a negative result: we show that
both linear Zero-Forcing (ZF) and linear Minimum Mean-Square Error (MMSE)
receivers achieve the same DMT, which is largely suboptimal even in the case
where outer coding and decoding is performed across the antennas. We also
provide an approximate quantitative analysis of the markedly different behavior
of the MMSE and ZF receivers at finite rate and non-asymptotic SNR, and show
that while the ZF receiver achieves poor diversity at any finite rate, the MMSE
receiver error curve slope flattens out progressively, as the coding rate
increases.
When SNR is fixed and the number of antennas becomes large, we show that the
mutual information at the output of a MMSE or ZF linear receiver has
fluctuations that converge in distribution to a Gaussian random variable, whose
mean and variance can be characterized in closed form. This analysis extends to
the linear receiver case a well-known result previously obtained for the
optimal receiver. Simulations reveal that the asymptotic analysis captures
accurately the outage behavior of systems even with a moderate number of
antennas.
|
0810.1103
|
Channel and Multiuser Diversities in Wireless Systems: Delay-Energy
Tradeoff
|
cs.IT math.IT
|
We consider a communication system with multi-access fading channel. Each
user in the system requires certain rate guarantee. Our main contribution is to
devise a scheduling scheme called "Opportunistic Super-position Coding" that
satisfies the users' rate requirements. Using mean-field analysis, i.e., when
the number of users go to infinity, we analytically show that the energy
required to guarantee the required user rate can be made as small as required
at the cost of a higher delay ("delay-energy tradeoff"). We explicitly compute
the delay under the proposed scheduling policy and discuss how delay
differentiation can be achieved. We extend the results to multi-band
multi-access channel. Finally, all the results can be generalized in a
straightforward fashion to broadcast channel due to the AWGN
multiaccess-broadcast duality.
|
0810.1105
|
Low-Density Parity-Check Codes Which Can Correct Three Errors Under
Iterative Decoding
|
cs.IT math.IT
|
In this paper, we give necessary and sufficient conditions for low-density
parity-check (LDPC) codes with column-weight three to correct three errors when
decoded using hard-decision message-passing decoding. Additionally, we give
necessary and sufficient conditions for column-weight-four codes to correct
three errors in four iterations of hard-decision message-passing decoding. We
then give a construction technique which results in codes satisfying these
conditions. We also provide numerical assessment of code performance via
simulation results.
|
0810.1119
|
Gaussian Belief Propagation for Solving Systems of Linear Equations:
Theory and Application
|
cs.IT math.IT
|
The canonical problem of solving a system of linear equations arises in
numerous contexts in information theory, communication theory, and related
fields. In this contribution, we develop a solution based upon Gaussian belief
propagation (GaBP) that does not involve direct matrix inversion. The iterative
nature of our approach allows for a distributed message-passing implementation
of the solution algorithm. We address the properties of the GaBP solver,
including convergence, exactness, computational complexity, message-passing
efficiency and its relation to classical solution methods. We use numerical
examples and applications, like linear detection, to illustrate these
properties through the use of computer simulations. This empirical study
demonstrates the attractiveness (e.g., faster convergence rate) of the proposed
GaBP solver in comparison to conventional linear-algebraic iterative solution
methods.
|
0810.1186
|
On-the-fly Macros
|
cs.AI
|
We present a domain-independent algorithm that computes macros in a novel
way. Our algorithm computes macros "on-the-fly" for a given set of states and
does not require previously learned or inferred information, nor prior domain
knowledge. The algorithm is used to define new domain-independent tractable
classes of classical planning that are proved to include \emph{Blocksworld-arm}
and \emph{Towers of Hanoi}.
|
0810.1187
|
Interference Alignment for Secrecy
|
cs.IT math.IT
|
This paper studies the frequency/time selective $K$-user Gaussian
interference channel with secrecy constraints. Two distinct models, namely the
interference channel with confidential messages and the one with an external
eavesdropper, are analyzed. The key difference between the two models is the
lack of channel state information (CSI) about the external eavesdropper. Using
interference alignment along with secrecy pre-coding, it is shown that each
user can achieve non-zero secure Degrees of Freedom (DoF) for both cases. More
precisely, the proposed coding scheme achieves $\frac{K-2}{2K-2}$ secure DoF
{\em with probability one} per user in the confidential messages model. For the
external eavesdropper scenario, on the other hand, it is shown that each user
can achieve $\frac{K-2}{2K}$ secure DoF {\em in the ergodic setting}.
Remarkably, these results establish the {\em positive impact} of interference
on the secrecy capacity region of wireless networks.
|
0810.1197
|
Construction of Near-Optimum Burst Erasure Correcting Low-Density
Parity-Check Codes
|
cs.IT math.IT
|
In this paper, a simple, general-purpose and effective tool for the design of
low-density parity-check (LDPC) codes for iterative correction of bursts of
erasures is presented. The design method consists in starting from the
parity-check matrix of an LDPC code and developing an optimized parity-check
matrix, with the same performance on the memory-less erasure channel, and
suitable also for the iterative correction of single bursts of erasures. The
parity-check matrix optimization is performed by an algorithm called pivot
searching and swapping (PSS) algorithm, which executes permutations of
carefully chosen columns of the parity-check matrix, after a local analysis of
particular variable nodes called stopping set pivots. This algorithm can be in
principle applied to any LDPC code. If the input parity-check matrix is
designed for achieving good performance on the memory-less erasure channel,
then the code obtained after the application of the PSS algorithm provides good
joint correction of independent erasures and single erasure bursts. Numerical
results are provided in order to show the effectiveness of the PSS algorithm
when applied to different categories of LDPC codes.
|
0810.1199
|
Une grammaire formelle du cr\'eole martiniquais pour la g\'en\'eration
automatique
|
cs.CL
|
In this article, some first elements of a computational modelling of the
grammar of the Martiniquese French Creole dialect are presented. The sources of
inspiration for the modelling is the functional description given by Damoiseau
(1984), and Pinalie's & Bernabe's (1999) grammar manual. Based on earlier works
in text generation (Vaillant, 1997), a unification grammar formalism, namely
Tree Adjoining Grammars (TAG), and a modelling of lexical functional categories
based on syntactic and semantic properties, are used to implement a grammar of
Martiniquese Creole which is used in a prototype of text generation system. One
of the main applications of the system could be its use as a tool software
supporting the task of learning Creole as a second language. -- Nous
pr\'esenterons dans cette communication les premiers travaux de mod\'elisation
informatique d'une grammaire de la langue cr\'eole martiniquaise, en nous
inspirant des descriptions fonctionnelles de Damoiseau (1984) ainsi que du
manuel de Pinalie & Bernab\'e (1999). Prenant appui sur des travaux
ant\'erieurs en g\'en\'eration de texte (Vaillant, 1997), nous utilisons un
formalisme de grammaires d'unification, les grammaires d'adjonction d'arbres
(TAG d'apr\`es l'acronyme anglais), ainsi qu'une mod\'elisation de cat\'egories
lexicales fonctionnelles \`a base syntaxico-s\'emantique, pour mettre en oeuvre
une grammaire du cr\'eole martiniquais utilisable dans une maquette de
syst\`eme de g\'en\'eration automatique. L'un des int\'er\^ets principaux de ce
syst\`eme pourrait \^etre son utilisation comme logiciel outil pour l'aide \`a
l'apprentissage du cr\'eole en tant que langue seconde.
|
0810.1207
|
A Layered Grammar Model: Using Tree-Adjoining Grammars to Build a Common
Syntactic Kernel for Related Dialects
|
cs.CL
|
This article describes the design of a common syntactic description for the
core grammar of a group of related dialects. The common description does not
rely on an abstract sub-linguistic structure like a metagrammar: it consists in
a single FS-LTAG where the actual specific language is included as one of the
attributes in the set of attribute types defined for the features. When the
lang attribute is instantiated, the selected subset of the grammar is
equivalent to the grammar of one dialect. When it is not, we have a model of a
hybrid multidialectal linguistic system. This principle is used for a group of
creole languages of the West-Atlantic area, namely the French-based Creoles of
Haiti, Guadeloupe, Martinique and French Guiana.
|
0810.1212
|
Analyse spectrale des textes: d\'etection automatique des fronti\`eres
de langue et de discours
|
cs.CL cs.IR
|
We propose a theoretical framework within which information on the vocabulary
of a given corpus can be inferred on the basis of statistical information
gathered on that corpus. Inferences can be made on the categories of the words
in the vocabulary, and on their syntactical properties within particular
languages. Based on the same statistical data, it is possible to build matrices
of syntagmatic similarity (bigram transition matrices) or paradigmatic
similarity (probability for any pair of words to share common contexts). When
clustered with respect to their syntagmatic similarity, words tend to group
into sublanguage vocabularies, and when clustered with respect to their
paradigmatic similarity, into syntactic or semantic classes. Experiments have
explored the first of these two possibilities. Their results are interpreted in
the frame of a Markov chain modelling of the corpus' generative processe(s): we
show that the results of a spectral analysis of the transition matrix can be
interpreted as probability distributions of words within clusters. This method
yields a soft clustering of the vocabulary into sublanguages which contribute
to the generation of heterogeneous corpora. As an application, we show how
multilingual texts can be visually segmented into linguistically homogeneous
segments. Our method is specifically useful in the case of related languages
which happened to be mixed in corpora.
|
0810.1234
|
On Resource Allocation in Fading Multiple Access Channels - An Efficient
Approximate Projection Approach
|
cs.IT cs.NI math.IT math.OC
|
We consider the problem of rate and power allocation in a multiple-access
channel. Our objective is to obtain rate and power allocation policies that
maximize a general concave utility function of average transmission rates on
the information theoretic capacity region of the multiple-access channel. Our
policies does not require queue-length information. We consider several
different scenarios. First, we address the utility maximization problem in a
nonfading channel to obtain the optimal operating rates, and present an
iterative gradient projection algorithm that uses approximate projection. By
exploiting the polymatroid structure of the capacity region, we show that the
approximate projection can be implemented in time polynomial in the number of
users. Second, we consider resource allocation in a fading channel. Optimal
rate and power allocation policies are presented for the case that power
control is possible and channel statistics are available. For the case that
transmission power is fixed and channel statistics are unknown, we propose a
greedy rate allocation policy and provide bounds on the performance difference
of this policy and the optimal policy in terms of channel variations and
structure of the utility function. We present numerical results that
demonstrate superior convergence rate performance for the greedy policy
compared to queue-length based policies. In order to reduce the computational
complexity of the greedy policy, we present approximate rate allocation
policies which track the greedy policy within a certain neighborhood that is
characterized in terms of the speed of fading.
|
0810.1248
|
Resource Allocation in Multiple Access Channels
|
cs.IT cs.NI math.IT math.OC
|
We consider the problem of rate allocation in a Gaussian multiple-access
channel, with the goal of maximizing a utility function over transmission
rates. In contrast to the literature which focuses on linear utility functions,
we study general concave utility functions. We present a gradient projection
algorithm for this problem. Since the constraint set of the problem is
described by exponentially many constraints, methods that use exact projections
are computationally intractable. Therefore, we develop a new method that uses
approximate projections. We use the polymatroid structure of the capacity
region to show that the approximate projection can be implemented by a
recursive algorithm in time polynomial in the number of users. We further
propose another algorithm for implementing the approximate projections using
rate-splitting and show improved bounds on its convergence time.
|
0810.1253
|
Dynamic Rate Allocation in Fading Multiple-access Channels
|
cs.IT cs.NI math.IT math.OC
|
We consider the problem of rate allocation in a fading Gaussian
multiple-access channel (MAC) with fixed transmission powers. Our goal is to
maximize a general concave utility function of transmission rates over the
throughput capacity region. In contrast to earlier works in this context that
propose solutions where a potentially complex optimization problem must be
solved in every decision instant, we propose a low-complexity approximate rate
allocation policy and analyze the effect of temporal channel variations on its
utility performance. To the best of our knowledge, this is the first work that
studies the tracking capabilities of an approximate rate allocation scheme
under fading channel conditions. We build on an earlier work to present a new
rate allocation policy for a fading MAC that implements a low-complexity
approximate gradient projection iteration for each channel measurement, and
explicitly characterize the effect of the speed of temporal channel variations
on the tracking neighborhood of our policy. We further improve our results by
proposing an alternative rate allocation policy for which tighter bounds on the
size of the tracking neighborhood are derived. These proposed rate allocation
policies are computationally efficient in our setting since they implement a
single gradient projection iteration per channel measurement and each such
iteration relies on approximate projections which has polynomial-complexity in
the number of users.
|
0810.1260
|
Rate and Power Allocation in Fading Multiple Access Channels
|
cs.IT cs.NI math.IT math.OC
|
We consider the problem of rate and power allocation in a fading
multiple-access channel. Our objective is to obtain rate and power allocation
policies that maximize a utility function defined over average transmission
rates. In contrast with the literature, which focuses on the linear case, we
present results for general concave utility functions. We consider two cases.
In the first case, we assume that power control is possible and channel
statistics are known. In this case, we show that the optimal policies can be
obtained greedily by maximizing a linear utility function at each channel
state. In the second case, we assume that power control is not possible and
channel statistics are not available. In this case, we define a greedy rate
allocation policy and provide upper bounds on the performance difference
between the optimal and the greedy policy. Our bounds highlight the dependence
of the performance difference on the channel variations and the structure of
the utility function.
|
0810.1261
|
Soft Uncoupling of Markov Chains for Permeable Language Distinction: A
New Algorithm
|
cs.CL cs.IR
|
Without prior knowledge, distinguishing different languages may be a hard
task, especially when their borders are permeable. We develop an extension of
spectral clustering -- a powerful unsupervised classification toolbox -- that
is shown to resolve accurately the task of soft language distinction. At the
heart of our approach, we replace the usual hard membership assignment of
spectral clustering by a soft, probabilistic assignment, which also presents
the advantage to bypass a well-known complexity bottleneck of the method.
Furthermore, our approach relies on a novel, convenient construction of a
Markov chain out of a corpus. Extensive experiments with a readily available
system clearly display the potential of the method, which brings a visually
appealing soft distinction of languages that may define altogether a whole
corpus.
|
0810.1267
|
Information Theory vs. Queueing Theory for Resource Allocation in
Multiple Access Channels
|
cs.IT cs.NI math.IT math.OC
|
We consider the problem of rate allocation in a fading Gaussian
multiple-access channel with fixed transmission powers. The goal is to maximize
a general concave utility function of the expected achieved rates of the users.
There are different approaches to this problem in the literature. From an
information theoretic point of view, rates are allocated only by using the
channel state information. The queueing theory approach utilizes the global
queue-length information for rate allocation to guarantee throughput optimality
as well as maximizing a utility function of the rates. In this work, we make a
connection between these two approaches by showing that the information
theoretic capacity region of a multiple-access channel and its stability region
are equivalent. Moreover, our numerical results show that a simple greedy
policy which does not use the queue-length information can outperform
queue-length based policies in terms of convergence rate and fairness.
|
0810.1268
|
Bi-directional half-duplex protocols with multiple relays
|
cs.IT math.IT
|
In a bi-directional relay channel, two nodes wish to exchange independent
messages over a shared wireless half-duplex channel with the help of relays.
Recent work has considered information theoretic limits of the bi-directional
relay channel with a single relay. In this work we consider bi-directional
relaying with multiple relays. We derive achievable rate regions and outer
bounds for half-duplex protocols with multiple decode and forward relays and
compare these to the same protocols with amplify and forward relays in an
additive white Gaussian noise channel. We consider three novel classes of
half-duplex protocols: the (m,2) 2 phase protocol with m relays, the (m,3) 3
phase protocol with m relays, and general (m, t) Multiple Hops and Multiple
Relays (MHMR) protocols, where m is the total number of relays and 3<t< m+3 is
the number of temporal phases in the protocol. The (m,2) and (m,3) protocols
extend previous bi-directional relaying protocols for a single m=1 relay, while
the new (m,t) protocol efficiently combines multi-hop routing with
message-level network coding. Finally, we provide a comprehensive treatment of
the MHMR protocols with decode and forward relaying and amplify and forward
relaying in the Gaussian noise, obtaining their respective achievable rate
regions, outer bounds and relative performance under different SNRs and relay
geometries, including an analytical comparison on the protocols at low and high
SNR.
|
0810.1319
|
ARQ-Based Secret Key Sharing
|
cs.IT cs.CR math.IT
|
This paper develops a novel framework for sharing secret keys using existing
Automatic Repeat reQuest (ARQ) protocols. Our approach exploits the multi-path
nature of the wireless environment to hide the key from passive eavesdroppers.
The proposed framework does not assume the availability of any prior channel
state information (CSI) and exploits only the one bit ACK/NACK feedback from
the legitimate receiver. Compared with earlier approaches, the main innovation
lies in the distribution of key bits among multiple ARQ frames. Interestingly,
this idea allows for achieving a positive secrecy rate even when the
eavesdropper experiences more favorable channel conditions, on average, than
the legitimate receiver. In the sequel, we characterize the information
theoretic limits of the proposed schemes, develop low complexity explicit
implementations, and conclude with numerical results that validate our
theoretical claims.
|
0810.1424
|
"Real" Slepian-Wolf Codes
|
cs.IT math.IT
|
We provide a novel achievability proof of the Slepian-Wolf theorem for i.i.d.
sources over finite alphabets. We demonstrate that random codes that are linear
over the real field achieve the classical Slepian-Wolf rate-region. For finite
alphabets we show that typicality decoding is equivalent to solving an integer
program. Minimum entropy decoding is also shown to achieve exponentially small
probability of error. The techniques used may be of independent interest for
code design for a wide class of information theory problems, and for the field
of compressed sensing.
|
0810.1430
|
Blind Cognitive MAC Protocols
|
cs.NI cs.LG
|
We consider the design of cognitive Medium Access Control (MAC) protocols
enabling an unlicensed (secondary) transmitter-receiver pair to communicate
over the idle periods of a set of licensed channels, i.e., the primary network.
The objective is to maximize data throughput while maintaining the
synchronization between secondary users and avoiding interference with licensed
(primary) users. No statistical information about the primary traffic is
assumed to be available a-priori to the secondary user. We investigate two
distinct sensing scenarios. In the first, the secondary transmitter is capable
of sensing all the primary channels, whereas it senses one channel only in the
second scenario. In both cases, we propose MAC protocols that efficiently learn
the statistics of the primary traffic online. Our simulation results
demonstrate that the proposed blind protocols asymptotically achieve the
throughput obtained when prior knowledge of primary traffic statistics is
available.
|
0810.1571
|
An Analytical Model of Information Dissemination for a Gossip-based
Protocol
|
cs.DC cs.DM cs.IT cs.PF math.IT
|
We develop an analytical model of information dissemination for a gossiping
protocol that combines both pull and push approaches. With this model we
analyse how fast an item is replicated through a network, and how fast the item
spreads in the network, and how fast the item covers the network. We also
determine the optimal size of the exchange buffer, to obtain fast replication.
Our results are confirmed by large-scale simulation experiments.
|
0810.1628
|
Distributed Kalman Filter via Gaussian Belief Propagation
|
cs.IT math.IT
|
Recent result shows how to compute distributively and efficiently the linear
MMSE for the multiuser detection problem, using the Gaussian BP algorithm. In
the current work, we extend this construction, and show that operating this
algorithm twice on the matching inputs, has several interesting
interpretations. First, we show equivalence to computing one iteration of the
Kalman filter. Second, we show that the Kalman filter is a special case of the
Gaussian information bottleneck algorithm, when the weight parameter $\beta =
1$. Third, we discuss the relation to the Affine-scaling interior-point method
and show it is a special case of Kalman filter.
Besides of the theoretical interest of this linking estimation,
compression/clustering and optimization, we allow a single distributed
implementation of those algorithms, which is a highly practical and important
task in sensor and mobile ad-hoc networks. Application to numerous problem
domains includes collaborative signal processing and distributed allocation of
resources in a communication network.
|
0810.1631
|
Polynomial Linear Programming with Gaussian Belief Propagation
|
cs.IT math.IT
|
Interior-point methods are state-of-the-art algorithms for solving linear
programming (LP) problems with polynomial complexity. Specifically, the
Karmarkar algorithm typically solves LP problems in time O(n^{3.5}), where $n$
is the number of unknown variables. Karmarkar's celebrated algorithm is known
to be an instance of the log-barrier method using the Newton iteration. The
main computational overhead of this method is in inverting the Hessian matrix
of the Newton iteration. In this contribution, we propose the application of
the Gaussian belief propagation (GaBP) algorithm as part of an efficient and
distributed LP solver that exploits the sparse and symmetric structure of the
Hessian matrix and avoids the need for direct matrix inversion. This approach
shifts the computation from realm of linear algebra to that of probabilistic
inference on graphical models, thus applying GaBP as an efficient inference
engine. Our construction is general and can be used for any interior-point
algorithm which uses the Newton method, including non-linear program solvers.
|
0810.1648
|
A Gaussian Belief Propagation Solver for Large Scale Support Vector
Machines
|
cs.LG cs.IT math.IT
|
Support vector machines (SVMs) are an extremely successful type of
classification and regression algorithms. Building an SVM entails solving a
constrained convex quadratic programming problem, which is quadratic in the
number of training samples. We introduce an efficient parallel implementation
of an support vector regression solver, based on the Gaussian Belief
Propagation algorithm (GaBP).
In this paper, we demonstrate that methods from the complex system domain
could be utilized for performing efficient distributed computation. We compare
the proposed algorithm to previously proposed distributed and single-node SVM
solvers. Our comparison shows that the proposed algorithm is just as accurate
as these solvers, while being significantly faster, especially for large
datasets. We demonstrate scalability of the proposed algorithm to up to 1,024
computing nodes and hundreds of thousands of data points using an IBM Blue Gene
supercomputer. As far as we know, our work is the largest parallel
implementation of belief propagation ever done, demonstrating the applicability
of this algorithm for large scale distributed computing systems.
|
0810.1729
|
Gaussian Belief Propagation Based Multiuser Detection
|
cs.IT math.IT
|
In this work, we present a novel construction for solving the linear
multiuser detection problem using the Gaussian Belief Propagation algorithm.
Our algorithm yields an efficient, iterative and distributed implementation of
the MMSE detector. We compare our algorithm's performance to a recent result
and show an improved memory consumption, reduced computation steps and a
reduction in the number of sent messages. We prove that recent work by
Montanari et al. is an instance of our general algorithm, providing new
convergence results for both algorithms.
|
0810.1732
|
Introduction to Searching with Regular Expressions
|
cs.IR
|
The explosive rate of information growth and availability often makes it
increasingly difficult to locate information pertinent to your needs. These
problems are often compounded when keyword based search methodologies are not
adequate for describing the information you seek. In many instances,
information such as Web site URLs, phone numbers, etc. can often be better
identified through the use of a textual pattern than by keyword. For example,
many more phone numbers could be picked up by a search for the pattern (XXX)
XXX-XXXX, where X could be any digit, than would be by a search for any
specific phone number (i.e. the keyword approach). Programming languages
typically allow for the matching of textual patterns via the usage of regular
expressions. This tutorial will provide an introduction to the basics of
programming regular expressions as well as provide an introduction to how
regular expressions can be applied to data processing tasks such as information
extraction and search refinement.
|
0810.1735
|
Network Coding in a Multicast Switch
|
cs.NI cs.IT math.IT
|
The problem of serving multicast flows in a crossbar switch is considered.
Intra-flow linear network coding is shown to achieve a larger rate region than
the case without coding. A traffic pattern is presented which is achievable
with coding but requires a switch speedup when coding is not allowed. The rate
region with coding can be characterized in a simple graph-theoretic manner, in
terms of the stable set polytope of the "enhanced conflict graph". No such
graph-theoretic characterization is known for the case of fanout splitting
without coding.
The minimum speedup needed to achieve 100% throughput with coding is shown to
be upper bounded by the imperfection ratio of the enhanced conflict graph. When
applied to KxN switches with unicasts and broadcasts only, this gives a bound
of min{(2K-1)/K,2N/(N+1)} on the speedup. This shows that speedup, which is
usually implemented in hardware, can often be substituted by network coding,
which can be done in software.
Computing an offline schedule (using prior knowledge of the flow rates) is
reduced to fractional weighted graph coloring. A graph-theoretic online
scheduling algorithm (using only queue occupancy information) is also proposed,
that stabilizes the queues for all rates within the rate region.
|
0810.1736
|
Gaussian Belief Propagation Solver for Systems of Linear Equations
|
cs.IT math.IT
|
The canonical problem of solving a system of linear equations arises in
numerous contexts in information theory, communication theory, and related
fields. In this contribution, we develop a solution based upon Gaussian belief
propagation (GaBP) that does not involve direct matrix inversion. The iterative
nature of our approach allows for a distributed message-passing implementation
of the solution algorithm. We also address some properties of the GaBP solver,
including convergence, exactness, its max-product version and relation to
classical solution methods. The application example of decorrelation in CDMA is
used to demonstrate the faster convergence rate of the proposed solver in
comparison to conventional linear-algebraic iterative solution methods.
|
0810.1773
|
Finite Word Length Effects on Transmission Rate in Zero Forcing Linear
Precoding for Multichannel DSL
|
cs.IT math.IT
|
Crosstalk interference is the limiting factor in transmission over copper
lines. Crosstalk cancelation techniques show great potential for enabling the
next leap in DSL transmission rates. An important issue when implementing
crosstalk cancelation techniques in hardware is the effect of finite world
length on performance. In this paper we provide an analysis of the performance
of linear zero-forcing precoders, used for crosstalk compensation, in the
presence of finite word length errors. We quantify analytically the trade off
between precoder word length and transmission rate degradation. More
specifically, we prove a simple formula for the transmission rate loss as a
function of the number of bits used for precoding, the signal to noise ratio,
and the standard line parameters. We demonstrate, through simulations on real
lines, the accuracy of our estimates. Moreover, our results are stable in the
presence of channel estimation errors. Finally, we show how to use these
estimates as a design tool for DSL linear crosstalk precoders. For example, we
show that for standard VDSL2 precoded systems, 14 bits representation of the
precoder entries results in capacity loss below 1% for lines over 300m.
|
0810.1808
|
A Central Limit Theorem for the SINR at the LMMSE Estimator Output for
Large Dimensional Signals
|
cs.IT math.IT
|
This paper is devoted to the performance study of the Linear Minimum Mean
Squared Error estimator for multidimensional signals in the large dimension
regime. Such an estimator is frequently encountered in wireless communications
and in array processing, and the Signal to Interference and Noise Ratio (SINR)
at its output is a popular performance index. The SINR can be modeled as a
random quadratic form which can be studied with the help of large random matrix
theory, if one assumes that the dimension of the received and transmitted
signals go to infinity at the same pace. This paper considers the asymptotic
behavior of the SINR for a wide class of multidimensional signal models that
includes general multi-antenna as well as spread spectrum transmission models.
The expression of the deterministic approximation of the SINR in the large
dimension regime is recalled and the SINR fluctuations around this
deterministic approximation are studied. These fluctuations are shown to
converge in distribution to the Gaussian law in the large dimension regime, and
their variance is shown to decrease as the inverse of the signal dimension.
|
0810.1973
|
Alphabet Sizes of Auxiliary Variables in Canonical Inner Bounds
|
cs.IT math.IT
|
Alphabet size of auxiliary random variables in our canonical description is
derived. Our analysis improves upon estimates known in special cases, and
generalizes to an arbitrary multiterminal setup. The salient steps include
decomposition of constituent rate polytopes into orthants, translation of a
hyperplane till it becomes tangent to the achievable region at an extreme
point, and derivation of minimum auxiliary alphabet sizes based on
Caratheodory's theorem.
|
0810.1980
|
Error Exponents of Optimum Decoding for the Interference Channel
|
cs.IT math.IT
|
Exponential error bounds for the finite-alphabet interference channel (IFC)
with two transmitter-receiver pairs, are investigated under the random coding
regime. Our focus is on optimum decoding, as opposed to heuristic decoding
rules that have been used in previous works, like joint typicality decoding,
decoding based on interference cancellation, and decoding that considers the
interference as additional noise. Indeed, the fact that the actual interfering
signal is a codeword and not an i.i.d. noise process complicates the
application of conventional techniques to the performance analysis of the
optimum decoder. Using analytical tools rooted in statistical physics, we
derive a single letter expression for error exponents achievable under optimum
decoding and demonstrate strict improvement over error exponents obtainable
using suboptimal decoding rules, but which are amenable to more conventional
analysis.
|
0810.1991
|
A global physician-oriented medical information system
|
cs.CY cs.AI cs.DB
|
We propose to improve medical decision making and reduce global health care
costs by employing a free Internet-based medical information system with two
main target groups: practicing physicians and medical researchers. After
acquiring patients' consent, physicians enter medical histories, physiological
data and symptoms or disorders into the system; an integrated expert system can
then assist in diagnosis and statistical software provides a list of the most
promising treatment options and medications, tailored to the patient.
Physicians later enter information about the outcomes of the chosen treatments,
data the system uses to optimize future treatment recommendations. Medical
researchers can analyze the aggregate data to compare various drugs or
treatments in defined patient populations on a large scale.
|
0810.1997
|
Characterizing 1-Dof Henneberg-I graphs with efficient configuration
spaces
|
cs.CG cs.RO cs.SC
|
We define and study exact, efficient representations of realization spaces of
a natural class of underconstrained 2D Euclidean Distance Constraint
Systems(EDCS) or Frameworks based on 1-dof Henneberg-I graphs. Each
representation corresponds to a choice of parameters and yields a different
parametrized configuration space. Our notion of efficiency is based on the
algebraic complexities of sampling the configuration space and of obtaining a
realization from the sample (parametrized) configuration. Significantly, we
give purely combinatorial characterizations that capture (i) the class of
graphs that have efficient configuration spaces and (ii) the possible choices
of representation parameters that yield efficient configuration spaces for a
given graph. Our results automatically yield an efficient algorithm for
sampling realizations, without missing extreme or boundary realizations. In
addition, our results formally show that our definition of efficient
configuration space is robust and that our characterizations are tight. We
choose the class of 1-dof Henneberg-I graphs in order to take the next step in
a systematic and graded program of combinatorial characterizations of efficient
configuration spaces. In particular, the results presented here are the first
characterizations that go beyond graphs that have connected and convex
configuration spaces.
|
0810.2021
|
Visualization Optimization : Application to the RoboCup Rescue Domain
|
cs.GR cs.AI
|
In this paper we demonstrate the use of intelligent optimization
methodologies on the visualization optimization of virtual / simulated
environments. The problem of automatic selection of an optimized set of views,
which better describes an on-going simulation over a virtual environment is
addressed in the context of the RoboCup Rescue Simulation domain. A generic
architecture for optimization is proposed and described. We outline the
possible extensions of this architecture and argue on how several problems
within the fields of Interactive Rendering and Visualization can benefit from
it.
|
0810.2046
|
Modeling of Social Transitions Using Intelligent Systems
|
cs.AI
|
In this study, we reproduce two new hybrid intelligent systems, involve three
prominent intelligent computing and approximate reasoning methods: Self
Organizing feature Map (SOM), Neruo-Fuzzy Inference System and Rough Set Theory
(RST),called SONFIS and SORST. We show how our algorithms can be construed as a
linkage of government-society interactions, where government catches various
states of behaviors: solid (absolute) or flexible. So, transition of society,
by changing of connectivity parameters (noise) from order to disorder is
inferred.
|
0810.2133
|
Diversity-Multiplexing Tradeoff of the Half-Duplex Relay Channel
|
cs.IT math.IT
|
We show that the diversity-multiplexing tradeoff of a half-duplex
single-relay channel with identically distributed Rayleigh fading channel gains
meets the 2 by 1 MISO bound. We generalize the result to the case when there
are N non-interfering relays and show that the diversity-multiplexing tradeoff
is equal to the N + 1 by 1 MISO bound.
|
0810.2144
|
Asymptotics of Entropy Rate in Special Families of Hidden Markov Chains
|
cs.IT math.IT
|
We derive an asymptotic formula for entropy rate of a hidden Markov chain
around a "weak Black Hole". We also discuss applications of the asymptotic
formula to the asymptotic behaviors of certain channels.
|
0810.2164
|
Joint source-channel coding via statistical mechanics: thermal
equilibrium between the source and the channel
|
cs.IT math.IT
|
We examine the classical joint source--channel coding problem from the
viewpoint of statistical physics and demonstrate that in the random coding
regime, the posterior probability distribution of the source given the channel
output is dominated by source sequences, which exhibit a behavior that is
highly parallel to that of thermal equilibrium between two systems of particles
that exchange energy, where one system corresponds to the source and the other
corresponds to the channel. The thermodynamical entopies of the dual physical
problem are analogous to conditional and unconditional Shannon entropies of the
source, and so, their balance in thermal equilibrium yields a simple formula
for the mutual information between the source and the channel output, that is
induced by the typical code in an ensemble of joint source--channel codes under
certain conditions. We also demonstrate how our results can be used in
applications, like the wiretap channel, and how can it be extended to multiuser
scenarios, like that of the multiple access channel.
|
0810.2208
|
Multipath Channels of Unbounded Capacity
|
cs.IT math.IT
|
The capacity of discrete-time, noncoherent, multipath fading channels is
considered. It is shown that if the variances of the path gains decay faster
than exponentially, then capacity is unbounded in the transmit power.
|
0810.2311
|
Non-Negative Matrix Factorization, Convexity and Isometry
|
cs.AI cs.CV
|
In this paper we explore avenues for improving the reliability of
dimensionality reduction methods such as Non-Negative Matrix Factorization
(NMF) as interpretive exploratory data analysis tools. We first explore the
difficulties of the optimization problem underlying NMF, showing for the first
time that non-trivial NMF solutions always exist and that the optimization
problem is actually convex, by using the theory of Completely Positive
Factorization. We subsequently explore four novel approaches to finding
globally-optimal NMF solutions using various ideas from convex optimization. We
then develop a new method, isometric NMF (isoNMF), which preserves
non-negativity while also providing an isometric embedding, simultaneously
achieving two properties which are helpful for interpretation. Though it
results in a more difficult optimization problem, we show experimentally that
the resulting method is scalable and even achieves more compact spectra than
standard NMF.
|
0810.2323
|
On Outage and Error Rate Analysis of the Ordered V-BLAST
|
cs.IT math.IT
|
Outage and error rate performance of the ordered BLAST with more than 2
transmit antennas is evaluated for i.i.d. Rayleigh fading channels. A number of
lower and upper bounds on the 1st step outage probability at any SNR are
derived, which are further used to obtain accurate approximations to average
block and total error rates. For m Tx antennas, the effect of the optimal
ordering at the first step is an m-fold SNR gain. As m increases to infinity,
the BLER decreases to zero, which is a manifestation of the space-time
autocoding effect in the V-BLAST. While the sub-optimal ordering (based on the
before-projection SNR) suffers a few dB SNR penalty compared to the optimal
one, it has a lower computational complexity and a 3 dB SNR gain compared to
the unordered V-BLAST and can be an attractive solution for
low-complexity/low-energy systems. Uncoded D-BLAST exhibits the same outage and
error rate performance as that of the V-BLAST. An SNR penalty of the linear
receiver interfaces compared to the BLAST is also evaluated.
|
0810.2336
|
A Mordell Inequality for Lattices over Maximal Orders
|
math.MG cs.IT math.IT math.NT
|
In this paper we prove an analogue of Mordell's inequality for lattices in
finite-dimensional complex or quaternionic Hermitian space that are modules
over a maximal order in an imaginary quadratic number field or a totally
definite rational quaternion algebra. This inequality implies that the
16-dimensional Barnes-Wall lattice has optimal density among all 16-dimensional
lattices with Hurwitz structures.
|
0810.2352
|
Interference Channels with Correlated Receiver Side Information
|
cs.IT math.IT
|
The problem of joint source-channel coding in transmitting independent
sources over interference channels with correlated receiver side information is
studied. When each receiver has side information correlated with its own
desired source, it is shown that source-channel code separation is optimal.
When each receiver has side information correlated with the interfering source,
sufficient conditions for reliable transmission are provided based on a joint
source-channel coding scheme using the superposition encoding and partial
decoding idea of Han and Kobayashi. When the receiver side information is a
deterministic function of the interfering source, source-channel code
separation is again shown to be optimal. As a special case, for a class of
Z-interference channels, when the side information of the receiver facing
interference is a deterministic function of the interfering source, necessary
and sufficient conditions for reliable transmission are provided in the form of
single letter expressions. As a byproduct of these joint source-channel coding
results, the capacity region of a class of Z-channels with degraded message
sets is also provided.
|
0810.2390
|
Efficient Pattern Matching on Binary Strings
|
cs.DS cs.IR
|
The binary string matching problem consists in finding all the occurrences of
a pattern in a text where both strings are built on a binary alphabet. This is
an interesting problem in computer science, since binary data are omnipresent
in telecom and computer network applications. Moreover the problem finds
applications also in the field of image processing and in pattern matching on
compressed texts. Recently it has been shown that adaptations of classical
exact string matching algorithms are not very efficient on binary data. In this
paper we present two efficient algorithms for the problem adapted to completely
avoid any reference to bits allowing to process pattern and text byte by byte.
Experimental results show that the new algorithms outperform existing solutions
in most cases.
|
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