13,695 research outputs found
Capacity Bounds for a Class of Interference Relay Channels
The capacity of a class of Interference Relay Channels (IRC) -the Injective
Semideterministic IRC where the relay can only observe one of the sources- is
investigated. We first derive a novel outer bound and two inner bounds which
are based on a careful use of each of the available cooperative strategies
together with the adequate interference decoding technique. The outer bound
extends Telatar and Tse's work while the inner bounds contain several known
results in the literature as special cases. Our main result is the
characterization of the capacity region of the Gaussian class of IRCs studied
within a fixed number of bits per dimension -constant gap. The proof relies on
the use of the different cooperative strategies in specific SNR regimes due to
the complexity of the schemes. As a matter of fact, this issue reveals the
complex nature of the Gaussian IRC where the combination of a single coding
scheme for the Gaussian relay and interference channel may not lead to a good
coding scheme for this problem, even when the focus is only on capacity to
within a constant gap over all possible fading statistics.Comment: 23 pages, 6 figures. Submitted to IEEE Transactions on Information
Theory (revised version
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
Incremental Relaying for the Gaussian Interference Channel with a Degraded Broadcasting Relay
This paper studies incremental relay strategies for a two-user Gaussian
relay-interference channel with an in-band-reception and
out-of-band-transmission relay, where the link between the relay and the two
receivers is modelled as a degraded broadcast channel. It is shown that
generalized hash-and-forward (GHF) can achieve the capacity region of this
channel to within a constant number of bits in a certain weak relay regime,
where the transmitter-to-relay link gains are not unboundedly stronger than the
interference links between the transmitters and the receivers. The GHF relaying
strategy is ideally suited for the broadcasting relay because it can be
implemented in an incremental fashion, i.e., the relay message to one receiver
is a degraded version of the message to the other receiver. A
generalized-degree-of-freedom (GDoF) analysis in the high signal-to-noise ratio
(SNR) regime reveals that in the symmetric channel setting, each common relay
bit can improve the sum rate roughly by either one bit or two bits
asymptotically depending on the operating regime, and the rate gain can be
interpreted as coming solely from the improvement of the common message rates,
or alternatively in the very weak interference regime as solely coming from the
rate improvement of the private messages. Further, this paper studies an
asymmetric case in which the relay has only a single single link to one of the
destinations. It is shown that with only one relay-destination link, the
approximate capacity region can be established for a larger regime of channel
parameters. Further, from a GDoF point of view, the sum-capacity gain due to
the relay can now be thought as coming from either signal relaying only, or
interference forwarding only.Comment: To appear in IEEE Trans. on Inf. 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
Degrees of Freedom of Two-Hop Wireless Networks: "Everyone Gets the Entire Cake"
We show that fully connected two-hop wireless networks with K sources, K
relays and K destinations have K degrees of freedom both in the case of
time-varying channel coefficients and in the case of constant channel
coefficients (in which case the result holds for almost all values of constant
channel coefficients). Our main contribution is a new achievability scheme
which we call Aligned Network Diagonalization. This scheme allows the data
streams transmitted by the sources to undergo a diagonal linear transformation
from the sources to the destinations, thus being received free of interference
by their intended destination. In addition, we extend our scheme to multi-hop
networks with fully connected hops, and multi-hop networks with MIMO nodes, for
which the degrees of freedom are also fully characterized.Comment: Presented at the 2012 Allerton Conference. Submitted to IEEE
Transactions on Information Theor
Interference Mitigation Through Limited Receiver Cooperation: Symmetric Case
Interference is a major issue that limits the performance in wireless
networks, and cooperation among receivers can help mitigate interference by
forming distributed MIMO systems. The rate at which receivers cooperate,
however, is limited in most scenarios. How much interference can one bit of
receiver cooperation mitigate? In this paper, we study the two-user Gaussian
interference channel with conferencing decoders to answer this question in a
simple setting. We characterize the fundamental gain from cooperation: at high
SNR, when INR is below 50% of SNR in dB scale, one-bit cooperation per
direction buys roughly one-bit gain per user until full receiver cooperation
performance is reached, while when INR is between 67% and 200% of SNR in dB
scale, one-bit cooperation per direction buys roughly half-bit gain per user.
The conclusion is drawn based on the approximate characterization of the
symmetric capacity in the symmetric set-up. We propose strategies achieving the
symmetric capacity universally to within 3 bits. The strategy consists of two
parts: (1) the transmission scheme, where superposition encoding with a simple
power split is employed, and (2) the cooperative protocol, where
quantize-binning is used for relaying.Comment: To appear in IEEE Information Theory Workshop, Taormina, October
2009. Final versio
Amplify-and-Forward in Wireless Relay Networks
A general class of wireless relay networks with a single source-destination
pair is considered. Intermediate nodes in the network employ an
amplify-and-forward scheme to relay their input signals. In this case the
overall input-output channel from the source via the relays to the destination
effectively behaves as an intersymbol interference channel with colored noise.
Unlike previous work we formulate the problem of the maximum achievable rate in
this setting as an optimization problem with no assumption on the network size,
topology, and received signal-to-noise ratio. Previous work considered only
scenarios wherein relays use all their power to amplify their received signals.
We demonstrate that this may not always maximize the maximal achievable rate in
amplify-and-forward relay networks. The proposed formulation allows us to not
only recover known results on the performance of the amplify-and-forward
schemes for some simple relay networks but also characterize the performance of
more complex amplify-and-forward relay networks which cannot be addressed in a
straightforward manner using existing approaches.
Using cut-set arguments, we derive simple upper bounds on the capacity of
general wireless relay networks. Through various examples, we show that a large
class of amplify-and-forward relay networks can achieve rates within a constant
factor of these upper bounds asymptotically in network parameters.Comment: Minor revision: fixed a typo in eqn. reference, changed the
formatting. 30 pages, 8 figure
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