7,721 research outputs found
Retrospective Interference Alignment
We explore similarities and differences in recent works on blind interference
alignment under different models such as staggered block fading model and the
delayed CSIT model. In particular we explore the possibility of achieving
interference alignment with delayed CSIT when the transmitters are distributed.
Our main contribution is an interference alignment scheme, called retrospective
interference alignment in this work, that is specialized to settings with
distributed transmitters. With this scheme we show that the 2 user X channel
with only delayed channel state information at the transmitters can achieve 8/7
DoF, while the interference channel with 3 users is able to achieve 9/8 DoF. We
also consider another setting where delayed channel output feedback is
available to transmitters. In this setting the X channel and the 3 user
interference channel are shown to achieve 4/3 and 6/5 DoF, respectively
Secure Degrees of Freedom of MIMO X-Channels with Output Feedback and Delayed CSIT
We investigate the problem of secure transmission over a two-user multi-input
multi-output (MIMO) X-channel in which channel state information is provided
with one-unit delay to both transmitters (CSIT), and each receiver feeds back
its channel output to a different transmitter. We refer to this model as MIMO
X-channel with asymmetric output feedback and delayed CSIT. The transmitters
are equipped with M-antennas each, and the receivers are equipped with
N-antennas each. For this model, accounting for both messages at each receiver,
we characterize the optimal sum secure degrees of freedom (SDoF) region. We
show that, in presence of asymmetric output feedback and delayed CSIT, the sum
SDoF region of the MIMO X-channel is same as the SDoF region of a two-user MIMO
BC with 2M-antennas at the transmitter, N-antennas at each receiver and delayed
CSIT. This result shows that, upon availability of asymmetric output feedback
and delayed CSIT, there is no performance loss in terms of sum SDoF due to the
distributed nature of the transmitters. Next, we show that this result also
holds if only output feedback is conveyed to the transmitters, but in a
symmetric manner, i.e., each receiver feeds back its output to both
transmitters and no CSIT. We also study the case in which only asymmetric
output feedback is provided to the transmitters, i.e., without CSIT, and derive
a lower bound on the sum SDoF for this model. Furthermore, we specialize our
results to the case in which there are no security constraints. In particular,
similar to the setting with security constraints, we show that the optimal sum
DoF region of the (M,M,N,N)--MIMO X-channel with asymmetric output feedback and
delayed CSIT is same as the DoF region of a two-user MIMO BC with 2M-antennas
at the transmitter, N-antennas at each receiver, and delayed CSIT. We
illustrate our results with some numerical examples.Comment: To Appear in IEEE Transactions on Information Forensics and Securit
Capacity Gain from Two-Transmitter and Two-Receiver Cooperation
Capacity improvement from transmitter and receiver cooperation is
investigated in a two-transmitter, two-receiver network with phase fading and
full channel state information available at all terminals. The transmitters
cooperate by first exchanging messages over an orthogonal transmitter
cooperation channel, then encoding jointly with dirty paper coding. The
receivers cooperate by using Wyner-Ziv compress-and-forward over an analogous
orthogonal receiver cooperation channel. To account for the cost of
cooperation, the allocation of network power and bandwidth among the data and
cooperation channels is studied. It is shown that transmitter cooperation
outperforms receiver cooperation and improves capacity over non-cooperative
transmission under most operating conditions when the cooperation channel is
strong. However, a weak cooperation channel limits the transmitter cooperation
rate; in this case receiver cooperation is more advantageous.
Transmitter-and-receiver cooperation offers sizable additional capacity gain
over transmitter-only cooperation at low SNR, whereas at high SNR transmitter
cooperation alone captures most of the cooperative capacity improvement.Comment: Accepted for publication in IEEE Transactions on Information Theor
The Impact of CSI and Power Allocation on Relay Channel Capacity and Cooperation Strategies
Capacity gains from transmitter and receiver cooperation are compared in a
relay network where the cooperating nodes are close together. Under
quasi-static phase fading, when all nodes have equal average transmit power
along with full channel state information (CSI), it is shown that transmitter
cooperation outperforms receiver cooperation, whereas the opposite is true when
power is optimally allocated among the cooperating nodes but only CSI at the
receiver (CSIR) is available. When the nodes have equal power with CSIR only,
cooperative schemes are shown to offer no capacity improvement over
non-cooperation under the same network power constraint. When the system is
under optimal power allocation with full CSI, the decode-and-forward
transmitter cooperation rate is close to its cut-set capacity upper bound, and
outperforms compress-and-forward receiver cooperation. Under fast Rayleigh
fading in the high SNR regime, similar conclusions follow. Cooperative systems
provide resilience to fading in channel magnitudes; however, capacity becomes
more sensitive to power allocation, and the cooperating nodes need to be closer
together for the decode-and-forward scheme to be capacity-achieving. Moreover,
to realize capacity improvement, full CSI is necessary in transmitter
cooperation, while in receiver cooperation optimal power allocation is
essential.Comment: Accepted for publication in IEEE Transactions on Wireless
Communication
The Practical Challenges of Interference Alignment
Interference alignment (IA) is a revolutionary wireless transmission strategy
that reduces the impact of interference. The idea of interference alignment is
to coordinate multiple transmitters so that their mutual interference aligns at
the receivers, facilitating simple interference cancellation techniques. Since
IA's inception, researchers have investigated its performance and proposed
improvements, verifying IA's ability to achieve the maximum degrees of freedom
(an approximation of sum capacity) in a variety of settings, developing
algorithms for determining alignment solutions, and generalizing transmission
strategies that relax the need for perfect alignment but yield better
performance. This article provides an overview of the concept of interference
alignment as well as an assessment of practical issues including performance in
realistic propagation environments, the role of channel state information at
the transmitter, and the practicality of interference alignment in large
networks.Comment: submitted to IEEE Wireless Communications Magazin
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