576 research outputs found
On practical design for joint distributed source and network coding
This paper considers the problem of communicating correlated information from multiple source nodes over a network of noiseless channels to multiple destination nodes, where each destination node wants to recover all sources. The problem involves a joint consideration of distributed compression and network information relaying. Although the optimal rate region has been theoretically characterized, it was not clear how to design practical communication schemes with low complexity. This work provides a partial solution to this problem by proposing a low-complexity scheme for the special case with two sources whose correlation is characterized by a binary symmetric channel. Our scheme is based on a careful combination of linear syndrome-based Slepian-Wolf coding and random linear mixing (network coding). It is in general suboptimal; however, its low complexity and robustness to network dynamics make it suitable for practical implementation
Slepian-Wolf Coding Over Cooperative Relay Networks
This paper deals with the problem of multicasting a set of discrete
memoryless correlated sources (DMCS) over a cooperative relay network.
Necessary conditions with cut-set interpretation are presented. A \emph{Joint
source-Wyner-Ziv encoding/sliding window decoding} scheme is proposed, in which
decoding at each receiver is done with respect to an ordered partition of other
nodes. For each ordered partition a set of feasibility constraints is derived.
Then, utilizing the sub-modular property of the entropy function and a novel
geometrical approach, the results of different ordered partitions are
consolidated, which lead to sufficient conditions for our problem. The proposed
scheme achieves operational separation between source coding and channel
coding. It is shown that sufficient conditions are indeed necessary conditions
in two special cooperative networks, namely, Aref network and finite-field
deterministic network. Also, in Gaussian cooperative networks, it is shown that
reliable transmission of all DMCS whose Slepian-Wolf region intersects the
cut-set bound region within a constant number of bits, is feasible. In
particular, all results of the paper are specialized to obtain an achievable
rate region for cooperative relay networks which includes relay networks and
two-way relay networks.Comment: IEEE Transactions on Information Theory, accepte
Cache-Aided Coded Multicast for Correlated Sources
The combination of edge caching and coded multicasting is a promising
approach to improve the efficiency of content delivery over cache-aided
networks. The global caching gain resulting from content overlap distributed
across the network in current solutions is limited due to the increasingly
personalized nature of the content consumed by users. In this paper, the
cache-aided coded multicast problem is generalized to account for the
correlation among the network content by formulating a source compression
problem with distributed side information. A correlation-aware achievable
scheme is proposed and an upper bound on its performance is derived. It is
shown that considerable load reductions can be achieved, compared to state of
the art correlation-unaware schemes, when caching and delivery phases
specifically account for the correlation among the content files.Comment: In proceeding of IEEE International Symposium on Turbo Codes and
Iterative Information Processing (ISTC), 201
Broadcast Caching Networks with Two Receivers and Multiple Correlated Sources
The correlation among the content distributed across a cache-aided broadcast
network can be exploited to reduce the delivery load on the shared wireless
link. This paper considers a two-user three-file network with correlated
content, and studies its fundamental limits for the worst-case demand. A class
of achievable schemes based on a two-step source coding approach is proposed.
Library files are first compressed using Gray-Wyner source coding, and then
cached and delivered using a combination of correlation-unaware cache-aided
coded multicast schemes. The second step is interesting in its own right and
considers a multiple-request caching problem, whose solution requires coding in
the placement phase. A lower bound on the optimal peak rate-memory trade-off is
derived, which is used to evaluate the performance of the proposed scheme. It
is shown that for symmetric sources the two-step strategy achieves the lower
bound for large cache capacities, and it is within half of the joint entropy of
two of the sources conditioned on the third source for all other cache sizes.Comment: in Proceedings of Asilomar Conference on Signals, Systems and
Computers, Pacific Grove, California, November 201
Updating Content in Cache-Aided Coded Multicast
Motivated by applications to delivery of dynamically updated, but correlated
data in settings such as content distribution networks, and distributed file
sharing systems, we study a single source multiple destination network coded
multicast problem in a cache-aided network. We focus on models where the caches
are primarily located near the destinations, and where the source has no cache.
The source observes a sequence of correlated frames, and is expected to do
frame-by-frame encoding with no access to prior frames. We present a novel
scheme that shows how the caches can be advantageously used to decrease the
overall cost of multicast, even though the source encodes without access to
past data. Our cache design and update scheme works with any choice of network
code designed for a corresponding cache-less network, is largely decentralized,
and works for an arbitrary network. We study a convex relation of the
optimization problem that results form the overall cost function. The results
of the optimization problem determines the rate allocation and caching
strategies. Numerous simulation results are presented to substantiate the
theory developed.Comment: To Appear in IEEE Journal on Selected Areas in Communications:
Special Issue on Caching for Communication Systems and Network
Communicating the sum of sources over a network
We consider the network communication scenario, over directed acyclic
networks with unit capacity edges in which a number of sources each
holding independent unit-entropy information wish to communicate the sum
to a set of terminals . We show that in the case in which
there are only two sources or only two terminals, communication is possible if
and only if each source terminal pair is connected by at least a
single path. For the more general communication problem in which there are
three sources and three terminals, we prove that a single path connecting the
source terminal pairs does not suffice to communicate . We then
present an efficient encoding scheme which enables the communication of
for the three sources, three terminals case, given that each source
terminal pair is connected by {\em two} edge disjoint paths.Comment: 12 pages, IEEE JSAC: Special Issue on In-network
Computation:Exploring the Fundamental Limits (to appear
Correlation-Aware Distributed Caching and Coded Delivery
Cache-aided coded multicast leverages side information at wireless edge
caches to efficiently serve multiple groupcast demands via common multicast
transmissions, leading to load reductions that are proportional to the
aggregate cache size. However, the increasingly unpredictable and personalized
nature of the content that users consume challenges the efficiency of existing
caching-based solutions in which only exact content reuse is explored. This
paper generalizes the cache-aided coded multicast problem to a source
compression with distributed side information problem that specifically
accounts for the correlation among the content files. It is shown how joint
file compression during the caching and delivery phases can provide load
reductions that go beyond those achieved with existing schemes. This is
accomplished through a lower bound on the fundamental rate-memory trade-off as
well as a correlation-aware achievable scheme, shown to significantly
outperform state-of-the-art correlation-unaware solutions, while approaching
the limiting rate-memory trade-off.Comment: In proceeding of IEEE Information Theory Workshop (ITW), 201
Computation Over Gaussian Networks With Orthogonal Components
Function computation of arbitrarily correlated discrete sources over Gaussian
networks with orthogonal components is studied. Two classes of functions are
considered: the arithmetic sum function and the type function. The arithmetic
sum function in this paper is defined as a set of multiple weighted arithmetic
sums, which includes averaging of the sources and estimating each of the
sources as special cases. The type or frequency histogram function counts the
number of occurrences of each argument, which yields many important statistics
such as mean, variance, maximum, minimum, median, and so on. The proposed
computation coding first abstracts Gaussian networks into the corresponding
modulo sum multiple-access channels via nested lattice codes and linear network
coding and then computes the desired function by using linear Slepian-Wolf
source coding. For orthogonal Gaussian networks (with no broadcast and
multiple-access components), the computation capacity is characterized for a
class of networks. For Gaussian networks with multiple-access components (but
no broadcast), an approximate computation capacity is characterized for a class
of networks.Comment: 30 pages, 12 figures, submitted to IEEE Transactions on Information
Theor
Rank-Two Beamforming and Power Allocation in Multicasting Relay Networks
In this paper, we propose a novel single-group multicasting relay beamforming
scheme. We assume a source that transmits common messages via multiple
amplify-and-forward relays to multiple destinations. To increase the number of
degrees of freedom in the beamforming design, the relays process two received
signals jointly and transmit the Alamouti space-time block code over two
different beams. Furthermore, in contrast to the existing relay multicasting
scheme of the literature, we take into account the direct links from the source
to the destinations. We aim to maximize the lowest received quality-of-service
by choosing the proper relay weights and the ideal distribution of the power
resources in the network. To solve the corresponding optimization problem, we
propose an iterative algorithm which solves sequences of convex approximations
of the original non-convex optimization problem. Simulation results demonstrate
significant performance improvements of the proposed methods as compared with
the existing relay multicasting scheme of the literature and an algorithm based
on the popular semidefinite relaxation technique
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