19,260 research outputs found
Queue-Architecture and Stability Analysis in Cooperative Relay Networks
An abstraction of the physical layer coding using bit pipes that are coupled
through data-rates is insufficient to capture notions such as node cooperation
in cooperative relay networks. Consequently, network-stability analyses based
on such abstractions are valid for non-cooperative schemes alone and
meaningless for cooperative schemes. Motivated from this, this paper develops a
framework that brings the information-theoretic coding scheme together with
network-stability analysis. This framework does not constrain the system to any
particular achievable scheme, i.e., the relays can use any cooperative coding
strategy of its choice, be it amplify/compress/quantize or any
alter-and-forward scheme. The paper focuses on the scenario when coherence
duration is of the same order of the packet/codeword duration, the channel
distribution is unknown and the fading state is only known causally. The main
contributions of this paper are two-fold: first, it develops a low-complexity
queue-architecture to enable stable operation of cooperative relay networks,
and, second, it establishes the throughput optimality of a simple network
algorithm that utilizes this queue-architecture.Comment: 16 pages, 1 figur
Band Codes for Energy-Efficient Network Coding with Application to P2P Mobile Streaming
A key problem in random network coding (NC) lies in the complexity and energy
consumption associated with the packet decoding processes, which hinder its
application in mobile environments. Controlling and hence limiting such factors
has always been an important but elusive research goal, since the packet degree
distribution, which is the main factor driving the complexity, is altered in a
non-deterministic way by the random recombinations at the network nodes. In
this paper we tackle this problem proposing Band Codes (BC), a novel class of
network codes specifically designed to preserve the packet degree distribution
during packet encoding, ecombination and decoding. BC are random codes over
GF(2) that exhibit low decoding complexity, feature limited and controlled
degree distribution by construction, and hence allow to effectively apply NC
even in energy-constrained scenarios. In particular, in this paper we motivate
and describe our new design and provide a thorough analysis of its performance.
We provide numerical simulations of the performance of BC in order to validate
the analysis and assess the overhead of BC with respect to a onventional NC
scheme. Moreover, peer-to-peer media streaming experiments with a random-push
protocol show that BC reduce the decoding complexity by a factor of two, to a
point where NC-based mobile streaming to mobile devices becomes practically
feasible.Comment: To be published in IEEE Transacions on Multimedi
Evolutionary Approaches to Minimizing Network Coding Resources
We wish to minimize the resources used for network coding while achieving the
desired throughput in a multicast scenario. We employ evolutionary approaches,
based on a genetic algorithm, that avoid the computational complexity that
makes the problem NP-hard. Our experiments show great improvements over the
sub-optimal solutions of prior methods. Our new algorithms improve over our
previously proposed algorithm in three ways. First, whereas the previous
algorithm can be applied only to acyclic networks, our new method works also
with networks with cycles. Second, we enrich the set of components used in the
genetic algorithm, which improves the performance. Third, we develop a novel
distributed framework. Combining distributed random network coding with our
distributed optimization yields a network coding protocol where the resources
used for coding are optimized in the setup phase by running our evolutionary
algorithm at each node of the network. We demonstrate the effectiveness of our
approach by carrying out simulations on a number of different sets of network
topologies.Comment: 9 pages, 6 figures, accepted to the 26th Annual IEEE Conference on
Computer Communications (INFOCOM 2007
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures
The convolutional neural network (CNN), which is one of the deep learning
models, has seen much success in a variety of computer vision tasks. However,
designing CNN architectures still requires expert knowledge and a lot of trial
and error. In this paper, we attempt to automatically construct CNN
architectures for an image classification task based on Cartesian genetic
programming (CGP). In our method, we adopt highly functional modules, such as
convolutional blocks and tensor concatenation, as the node functions in CGP.
The CNN structure and connectivity represented by the CGP encoding method are
optimized to maximize the validation accuracy. To evaluate the proposed method,
we constructed a CNN architecture for the image classification task with the
CIFAR-10 dataset. The experimental result shows that the proposed method can be
used to automatically find the competitive CNN architecture compared with
state-of-the-art models.Comment: This is the revised version of the GECCO 2017 paper. The code of our
method is available at https://github.com/sg-nm/cgp-cn
Distributed Space-Time Coding Based on Adjustable Code Matrices for Cooperative MIMO Relaying Systems
An adaptive distributed space-time coding (DSTC) scheme is proposed for
two-hop cooperative MIMO networks. Linear minimum mean square error (MMSE)
receive filters and adjustable code matrices are considered subject to a power
constraint with an amplify-and-forward (AF) cooperation strategy. In the
proposed adaptive DSTC scheme, an adjustable code matrix obtained by a feedback
channel is employed to transform the space-time coded matrix at the relay node.
The effects of the limited feedback and the feedback errors are assessed.
Linear MMSE expressions are devised to compute the parameters of the adjustable
code matrix and the linear receive filters. Stochastic gradient (SG) and
least-squares (LS) algorithms are also developed with reduced computational
complexity. An upper bound on the pairwise error probability analysis is
derived and indicates the advantage of employing the adjustable code matrices
at the relay nodes. An alternative optimization algorithm for the adaptive DSTC
scheme is also derived in order to eliminate the need for the feedback. The
algorithm provides a fully distributed scheme for the adaptive DSTC at the
relay node based on the minimization of the error probability. Simulation
results show that the proposed algorithms obtain significant performance gains
as compared to existing DSTC schemes.Comment: 6 figure
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