174 research outputs found
Speeding up Future Video Distribution via Channel-Aware Caching-Aided Coded Multicast
Future Internet usage will be dominated by the consumption of a rich variety
of online multimedia services accessed from an exponentially growing number of
multimedia capable mobile devices. As such, future Internet designs will be
challenged to provide solutions that can deliver bandwidth-intensive,
delay-sensitive, on-demand video-based services over increasingly crowded,
bandwidth-limited wireless access networks. One of the main reasons for the
bandwidth stress facing wireless network operators is the difficulty to exploit
the multicast nature of the wireless medium when wireless users or access
points rarely experience the same channel conditions or access the same content
at the same time. In this paper, we present and analyze a novel wireless video
delivery paradigm based on the combined use of channel-aware caching and coded
multicasting that allows simultaneously serving multiple cache-enabled
receivers that may be requesting different content and experiencing different
channel conditions. To this end, we reformulate the caching-aided coded
multicast problem as a joint source-channel coding problem and design an
achievable scheme that preserves the cache-enabled multiplicative throughput
gains of the error-free scenario,by guaranteeing per-receiver rates unaffected
by the presence of receivers with worse channel conditions.Comment: 11 pages,6 figures,to appear in IEEE JSAC Special Issue on Video
Distribution over Future Interne
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
Multiple Multicasts with the Help of a Relay
The problem of simultaneous multicasting of multiple messages with the help
of a relay terminal is considered. In particular, a model is studied in which a
relay station simultaneously assists two transmitters in multicasting their
independent messages to two receivers. The relay may also have an independent
message of its own to multicast. As a first step to address this general model,
referred to as the compound multiple access channel with a relay (cMACr), the
capacity region of the multiple access channel with a "cognitive" relay is
characterized, including the cases of partial and rate-limited cognition. Then,
achievable rate regions for the cMACr model are presented based on
decode-and-forward (DF) and compress-and-forward (CF) relaying strategies.
Moreover, an outer bound is derived for the special case, called the cMACr
without cross-reception, in which each transmitter has a direct link to one of
the receivers while the connection to the other receiver is enabled only
through the relay terminal. The capacity region is characterized for a binary
modulo additive cMACr without cross-reception, showing the optimality of binary
linear block codes, thus highlighting the benefits of physical layer network
coding and structured codes. Results are extended to the Gaussian channel model
as well, providing achievable rate regions for DF and CF, as well as for a
structured code design based on lattice codes. It is shown that the performance
with lattice codes approaches the upper bound for increasing power, surpassing
the rates achieved by the considered random coding-based techniques.Comment: Submitted to Transactions on Information Theor
Multi-destination Aggregation with Binary Symmetric Broadcast Channel Based Coding in 802.11 WLANs
In this paper we consider the potential benefits of adopting a binary symmetric broadcast channel paradigm for multi-destination aggregation in 802.11 WLANs, as opposed to a more conventional packet erasure channel paradigm. We propose two approaches for multi-destination aggregation, i.e. superposition coding and a simpler time-sharing coding. Theoretical and simulation results for both unicast and multicast traffic demonstrate that increases in network throughput of more than 100% are possible over a wide range of network conditions and that the much simpler time-sharing scheme yields most of these gains and have minimal loss of performance. Importantly, these performance gains are achieved exclusively through software rather than hardware changes
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
Lecture Notes on Network Information Theory
These lecture notes have been converted to a book titled Network Information
Theory published recently by Cambridge University Press. This book provides a
significantly expanded exposition of the material in the lecture notes as well
as problems and bibliographic notes at the end of each chapter. The authors are
currently preparing a set of slides based on the book that will be posted in
the second half of 2012. More information about the book can be found at
http://www.cambridge.org/9781107008731/. The previous (and obsolete) version of
the lecture notes can be found at http://arxiv.org/abs/1001.3404v4/
Reliable Physical Layer Network Coding
When two or more users in a wireless network transmit simultaneously, their
electromagnetic signals are linearly superimposed on the channel. As a result,
a receiver that is interested in one of these signals sees the others as
unwanted interference. This property of the wireless medium is typically viewed
as a hindrance to reliable communication over a network. However, using a
recently developed coding strategy, interference can in fact be harnessed for
network coding. In a wired network, (linear) network coding refers to each
intermediate node taking its received packets, computing a linear combination
over a finite field, and forwarding the outcome towards the destinations. Then,
given an appropriate set of linear combinations, a destination can solve for
its desired packets. For certain topologies, this strategy can attain
significantly higher throughputs over routing-based strategies. Reliable
physical layer network coding takes this idea one step further: using
judiciously chosen linear error-correcting codes, intermediate nodes in a
wireless network can directly recover linear combinations of the packets from
the observed noisy superpositions of transmitted signals. Starting with some
simple examples, this survey explores the core ideas behind this new technique
and the possibilities it offers for communication over interference-limited
wireless networks.Comment: 19 pages, 14 figures, survey paper to appear in Proceedings of the
IEE
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