8,613 research outputs found
Capacity of a Class of Deterministic Relay Channels
The capacity of a class of deterministic relay channels with the transmitter
input X, the receiver output Y, the relay output Y_1 = f(X, Y), and a separate
communication link from the relay to the receiver with capacity R_0, is shown
to be
C(R_0) = \max_{p(x)} \min \{I(X;Y)+R_0, I(X;Y, Y_1) \}.
Thus every bit from the relay is worth exactly one bit to the receiver. Two
alternative coding schemes are presented that achieve this capacity. The first
scheme, ``hash-and-forward'', is based on a simple yet novel use of random
binning on the space of relay outputs, while the second scheme uses the usual
``compress-and-forward''. In fact, these two schemes can be combined together
to give a class of optimal coding schemes. As a corollary, this relay capacity
result confirms a conjecture by Ahlswede and Han on the capacity of a channel
with rate-limited state information at the decoder in the special case when the
channel state is recoverable from the channel input and the output.Comment: 17 pages, submitted to IEEE Transactions on Information Theor
A New Achievable Scheme for Interference Relay Channels
We establish an achievable rate region for discrete memoryless interference
relay channels that consist of two source-destination pairs and one or more
relays. We develop an achievable scheme combining Han-Kobayashi and noisy
network coding schemes. We apply our achievability to two cases. First, we
characterize the capacity region of a class of discrete memoryless interference
relay channels. This class naturally generalizes the injective deterministic
discrete memoryless interference channel by El Gamal and Costa and the
deterministic discrete memoryless relay channel with orthogonal receiver
components by Kim. Moreover, for the Gaussian interference relay channel with
orthogonal receiver components, we show that our scheme achieves a better sum
rate than that of noisy network coding.Comment: 18 pages, 4 figure
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
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 Results for Relay Channels with Confidential Messages
We consider a communication system where a relay helps transmission of
messages from {a} sender to {a} receiver. The relay is considered not only as a
helper but as a wire-tapper who can obtain some knowledge about transmitted
messages. In this paper we study a relay channel with confidential
messages(RCC), where a sender attempts to transmit common information to both a
receiver and a relay and also has private information intended for the receiver
and confidential to the relay. The level of secrecy of private information
confidential to the relay is measured by the equivocation rate, i.e., the
entropy rate of private information conditioned on channel outputs at the
relay. The performance measure of interest for the RCC is the rate triple that
includes the common rate, the private rate, and the equivocation rate as
components. The rate-equivocation region is defined by the set that consists of
all these achievable rate triples. In this paper we give two definitions of the
rate-equivocation region. We first define the rate-equivocation region in the
case of deterministic encoder and call it the deterministic rate-equivocation
region. Next, we define the rate-equivocation region in the case of stochastic
encoder and call it the stochastic rate-equivocation region. We derive explicit
inner and outer bounds for the above two regions. On the
deterministic/stochastic rate-equivocation region we present two classes of
relay channels where inner and outer bounds match. We also evaluate the
deterministic and stochastic rate-equivocation regions of the Gaussian RCC.Comment: 31 pages, 8 figure
On the Capacity Region of the Two-user Interference Channel with a Cognitive Relay
This paper considers a variation of the classical two-user interference
channel where the communication of two interfering source-destination pairs is
aided by an additional node that has a priori knowledge of the messages to be
transmitted, which is referred to as the it cognitive relay. For this
Interference Channel with a Cognitive Relay (ICCR) In particular, for the class
of injective semi-deterministic ICCRs, a sum-rate upper bound is derived for
the general memoryless ICCR and further tightened for the Linear Deterministic
Approximation (LDA) of the Gaussian noise channel at high SNR, which disregards
the noise and focuses on the interaction among the users' signals. The capacity
region of the symmetric LDA is completely characterized except for the regime
of moderately weak interference and weak links from the CR to the destinations.
The insights gained from the analysis of the LDA are then translated back to
the symmetric Gaussian noise channel (GICCR). For the symmetric GICCR, an
approximate characterization (to within a constant gap) of the capacity region
is provided for a parameter regime where capacity was previously unknown. The
approximately optimal scheme suggests that message cognition at a relay is
beneficial for interference management as it enables simultaneous over the air
neutralization of the interference at both destinations
A digital interface for Gaussian relay and interference networks: Lifting codes from the discrete superposition model
For every Gaussian network, there exists a corresponding deterministic
network called the discrete superposition network. We show that this discrete
superposition network provides a near-optimal digital interface for operating a
class consisting of many Gaussian networks in the sense that any code for the
discrete superposition network can be naturally lifted to a corresponding code
for the Gaussian network, while achieving a rate that is no more than a
constant number of bits lesser than the rate it achieves for the discrete
superposition network. This constant depends only on the number of nodes in the
network and not on the channel gains or SNR. Moreover the capacities of the two
networks are within a constant of each other, again independent of channel
gains and SNR. We show that the class of Gaussian networks for which this
interface property holds includes relay networks with a single
source-destination pair, interference networks, multicast networks, and the
counterparts of these networks with multiple transmit and receive antennas.
The code for the Gaussian relay network can be obtained from any code for the
discrete superposition network simply by pruning it. This lifting scheme
establishes that the superposition model can indeed potentially serve as a
strong surrogate for designing codes for Gaussian relay networks.
We present similar results for the K x K Gaussian interference network, MIMO
Gaussian interference networks, MIMO Gaussian relay networks, and multicast
networks, with the constant gap depending additionally on the number of
antennas in case of MIMO networks.Comment: Final versio
Deterministic Capacity of MIMO Relay Networks
The deterministic capacity of a relay network is the capacity of a network
when relays are restricted to transmitting \emph{reliable} information, that
is, (asymptotically) deterministic function of the source message. In this
paper it is shown that the deterministic capacity of a number of MIMO relay
networks can be found in the low power regime where \SNR\to0. This is
accomplished through deriving single letter upper bounds and finding the limit
of these as \SNR\to0. The advantage of this technique is that it overcomes
the difficulty of finding optimum distributions for mutual information.Comment: Submitted to IEEE Transactions on Information Theor
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