3,573 research outputs found
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
Nested Lattice Codes for Gaussian Relay Networks with Interference
In this paper, a class of relay networks is considered. We assume that, at a
node, outgoing channels to its neighbors are orthogonal, while incoming signals
from neighbors can interfere with each other. We are interested in the
multicast capacity of these networks. As a subclass, we first focus on Gaussian
relay networks with interference and find an achievable rate using a lattice
coding scheme. It is shown that there is a constant gap between our achievable
rate and the information theoretic cut-set bound. This is similar to the recent
result by Avestimehr, Diggavi, and Tse, who showed such an approximate
characterization of the capacity of general Gaussian relay networks. However,
our achievability uses a structured code instead of a random one. Using the
same idea used in the Gaussian case, we also consider linear finite-field
symmetric networks with interference and characterize the capacity using a
linear coding scheme.Comment: 23 pages, 5 figures, submitted to IEEE Transactions on Information
Theor
Computation Alignment: Capacity Approximation without Noise Accumulation
Consider several source nodes communicating across a wireless network to a
destination node with the help of several layers of relay nodes. Recent work by
Avestimehr et al. has approximated the capacity of this network up to an
additive gap. The communication scheme achieving this capacity approximation is
based on compress-and-forward, resulting in noise accumulation as the messages
traverse the network. As a consequence, the approximation gap increases
linearly with the network depth.
This paper develops a computation alignment strategy that can approach the
capacity of a class of layered, time-varying wireless relay networks up to an
approximation gap that is independent of the network depth. This strategy is
based on the compute-and-forward framework, which enables relays to decode
deterministic functions of the transmitted messages. Alone, compute-and-forward
is insufficient to approach the capacity as it incurs a penalty for
approximating the wireless channel with complex-valued coefficients by a
channel with integer coefficients. Here, this penalty is circumvented by
carefully matching channel realizations across time slots to create
integer-valued effective channels that are well-suited to compute-and-forward.
Unlike prior constant gap results, the approximation gap obtained in this paper
also depends closely on the fading statistics, which are assumed to be i.i.d.
Rayleigh.Comment: 36 pages, to appear in IEEE Transactions on Information Theor
Capacity of a Class of State-Dependent Orthogonal Relay Channels
The class of orthogonal relay channels in which the orthogonal channels
connecting the source terminal to the relay and the destination, and the relay
to the destination, depend on a state sequence, is considered. It is assumed
that the state sequence is fully known at the destination while it is not known
at the source or the relay. The capacity of this class of relay channels is
characterized, and shown to be achieved by the partial
decode-compress-and-forward (pDCF) scheme. Then the capacity of certain binary
and Gaussian state-dependent orthogonal relay channels are studied in detail,
and it is shown that the compress-and-forward (CF) and
partial-decode-and-forward (pDF) schemes are suboptimal in general. To the best
of our knowledge, this is the first single relay channel model for which the
capacity is achieved by pDCF, while pDF and CF schemes are both suboptimal.
Furthermore, it is shown that the capacity of the considered class of
state-dependent orthogonal relay channels is in general below the cut-set
bound. The conditions under which pDF or CF suffices to meet the cut-set bound,
and hence, achieve the capacity, are also derived.Comment: This paper has been accepted by IEEE Transactions on Information
Theor
Network Code Design for Orthogonal Two-hop Network with Broadcasting Relay: A Joint Source-Channel-Network Coding Approach
This paper addresses network code design for robust transmission of sources
over an orthogonal two-hop wireless network with a broadcasting relay. The
network consists of multiple sources and destinations in which each
destination, benefiting the relay signal, intends to decode a subset of the
sources. Two special instances of this network are orthogonal broadcast relay
channel and the orthogonal multiple access relay channel. The focus is on
complexity constrained scenarios, e.g., for wireless sensor networks, where
channel coding is practically imperfect. Taking a source-channel and network
coding approach, we design the network code (mapping) at the relay such that
the average reconstruction distortion at the destinations is minimized. To this
end, by decomposing the distortion into its components, an efficient design
algorithm is proposed. The resulting network code is nonlinear and
substantially outperforms the best performing linear network code. A motivating
formulation of a family of structured nonlinear network codes is also
presented. Numerical results and comparison with linear network coding at the
relay and the corresponding distortion-power bound demonstrate the
effectiveness of the proposed schemes and a promising research direction.Comment: 27 pages, 9 figures, Submited to IEEE Transaction on Communicatio
Cooperation with an Untrusted Relay: A Secrecy Perspective
We consider the communication scenario where a source-destination pair wishes
to keep the information secret from a relay node despite wanting to enlist its
help. For this scenario, an interesting question is whether the relay node
should be deployed at all. That is, whether cooperation with an untrusted relay
node can ever be beneficial. We first provide an achievable secrecy rate for
the general untrusted relay channel, and proceed to investigate this question
for two types of relay networks with orthogonal components. For the first
model, there is an orthogonal link from the source to the relay. For the second
model, there is an orthogonal link from the relay to the destination. For the
first model, we find the equivocation capacity region and show that answer is
negative. In contrast, for the second model, we find that the answer is
positive. Specifically, we show by means of the achievable secrecy rate based
on compress-and-forward, that, by asking the untrusted relay node to relay
information, we can achieve a higher secrecy rate than just treating the relay
as an eavesdropper. For a special class of the second model, where the relay is
not interfering itself, we derive an upper bound for the secrecy rate using an
argument whose net effect is to separate the eavesdropper from the relay. The
merit of the new upper bound is demonstrated on two channels that belong to
this special class. The Gaussian case of the second model mentioned above
benefits from this approach in that the new upper bound improves the previously
known bounds. For the Cover-Kim deterministic relay channel, the new upper
bound finds the secrecy capacity when the source-destination link is not worse
than the source-relay link, by matching with the achievable rate we present.Comment: IEEE Transactions on Information Theory, submitted October 2008,
revised October 2009. This is the revised versio
Stabilization of Linear Systems Over Gaussian Networks
The problem of remotely stabilizing a noisy linear time invariant plant over
a Gaussian relay network is addressed. The network is comprised of a sensor
node, a group of relay nodes and a remote controller. The sensor and the relay
nodes operate subject to an average transmit power constraint and they can
cooperate to communicate the observations of the plant's state to the remote
controller. The communication links between all nodes are modeled as Gaussian
channels. Necessary as well as sufficient conditions for mean-square
stabilization over various network topologies are derived. The sufficient
conditions are in general obtained using delay-free linear policies and the
necessary conditions are obtained using information theoretic tools. Different
settings where linear policies are optimal, asymptotically optimal (in certain
parameters of the system) and suboptimal have been identified. For the case
with noisy multi-dimensional sources controlled over scalar channels, it is
shown that linear time varying policies lead to minimum capacity requirements,
meeting the fundamental lower bound. For the case with noiseless sources and
parallel channels, non-linear policies which meet the lower bound have been
identified
Multiple Unicast Capacity of 2-Source 2-Sink Networks
We study the sum capacity of multiple unicasts in wired and wireless multihop
networks. With 2 source nodes and 2 sink nodes, there are a total of 4
independent unicast sessions (messages), one from each source to each sink node
(this setting is also known as an X network). For wired networks with arbitrary
connectivity, the sum capacity is achieved simply by routing. For wireless
networks, we explore the degrees of freedom (DoF) of multihop X networks with a
layered structure, allowing arbitrary number of hops, and arbitrary
connectivity within each hop. For the case when there are no more than two
relay nodes in each layer, the DoF can only take values 1, 4/3, 3/2 or 2, based
on the connectivity of the network, for almost all values of channel
coefficients. When there are arbitrary number of relays in each layer, the DoF
can also take the value 5/3 . Achievability schemes incorporate linear
forwarding, interference alignment and aligned interference neutralization
principles. Information theoretic converse arguments specialized for the
connectivity of the network are constructed based on the intuition from linear
dimension counting arguments.Comment: 6 pages, 7 figures, submitted to IEEE Globecom 201
- …