7,298 research outputs found
Achievable Rates for K-user Gaussian Interference Channels
The aim of this paper is to study the achievable rates for a user
Gaussian interference channels for any SNR using a combination of lattice and
algebraic codes. Lattice codes are first used to transform the Gaussian
interference channel (G-IFC) into a discrete input-output noiseless channel,
and subsequently algebraic codes are developed to achieve good rates over this
new alphabet. In this context, a quantity called efficiency is introduced which
reflects the effectiveness of the algebraic coding strategy. The paper first
addresses the problem of finding high efficiency algebraic codes. A combination
of these codes with Construction-A lattices is then used to achieve non trivial
rates for the original Gaussian interference channel.Comment: IEEE Transactions on Information Theory, 201
Robust Lattice Alignment for K-user MIMO Interference Channels with Imperfect Channel Knowledge
In this paper, we consider a robust lattice alignment design for K-user
quasi-static MIMO interference channels with imperfect channel knowledge. With
random Gaussian inputs, the conventional interference alignment (IA) method has
the feasibility problem when the channel is quasi-static. On the other hand,
structured lattices can create structured interference as opposed to the random
interference caused by random Gaussian symbols. The structured interference
space can be exploited to transmit the desired signals over the gaps. However,
the existing alignment methods on the lattice codes for quasi-static channels
either require infinite SNR or symmetric interference channel coefficients.
Furthermore, perfect channel state information (CSI) is required for these
alignment methods, which is difficult to achieve in practice. In this paper, we
propose a robust lattice alignment method for quasi-static MIMO interference
channels with imperfect CSI at all SNR regimes, and a two-stage decoding
algorithm to decode the desired signal from the structured interference space.
We derive the achievable data rate based on the proposed robust lattice
alignment method, where the design of the precoders, decorrelators, scaling
coefficients and interference quantization coefficients is jointly formulated
as a mixed integer and continuous optimization problem. The effect of imperfect
CSI is also accommodated in the optimization formulation, and hence the derived
solution is robust to imperfect CSI. We also design a low complex iterative
optimization algorithm for our robust lattice alignment method by using the
existing iterative IA algorithm that was designed for the conventional IA
method. Numerical results verify the advantages of the proposed robust lattice
alignment method
The Approximate Capacity of the Many-to-One and One-to-Many Gaussian Interference Channels
Recently, Etkin, Tse, and Wang found the capacity region of the two-user
Gaussian interference channel to within one bit/s/Hz. A natural goal is to
apply this approach to the Gaussian interference channel with an arbitrary
number of users. We make progress towards this goal by finding the capacity
region of the many-to-one and one-to-many Gaussian interference channels to
within a constant number of bits. The result makes use of a deterministic model
to provide insight into the Gaussian channel. The deterministic model makes
explicit the dimension of signal scale. A central theme emerges: the use of
lattice codes for alignment of interfering signals on the signal scale.Comment: 45 pages, 16 figures. Submitted to IEEE Transactions on Information
Theor
Lattice Codes for Many-to-One Interference Channels With and Without Cognitive Messages
A new achievable rate region is given for the Gaussian cognitive many-to-one
interference channel. The proposed novel coding scheme is based on the
compute-and-forward approach with lattice codes. Using the idea of decoding
sums of codewords, our scheme improves considerably upon the conventional
coding schemes which treat interference as noise or decode messages
simultaneously. Our strategy also extends directly to the usual many-to-one
interference channels without cognitive messages. Comparing to the usual
compute-and-forward scheme where a fixed lattice is used for the code
construction, the novel scheme employs scaled lattices and also encompasses key
ingredients of the existing schemes for the cognitive interference channel.
With this new component, our scheme achieves a larger rate region in general.
For some symmetric channel settings, new constant gap or capacity results are
established, which are independent of the number of users in the system.Comment: To appear in IEEE Transactions on Information Theor
Interference management for Interference Channels: Performance improvement and lattice techniques
This thesis focuses on interference management methods for interference channels, in particular on interference alignment. The aim is to contribute to the understanding of issues such as the performance of the interference alignment scheme and lattice codes for interference channels. Interference alignment is studied from two perspectives. One is the signal space perspective where precoding methods are designed to align the interference in half of the received subspace. Cadambe and Jafar found precoding matrices to achieve the theoretical degrees of freedom. However, using an interference suppression technique over the Cadambe and Jafar scheme, yields poor performance. Thus, in this thesis precoding methods such as singular value decomposition and Tomlinson-Harashima precoding are proposed to improve performance. The second perspective is on the signal scale, where structured codes are used to align interference. For this, lattice codes are suitable. In this research, the problem was initially approached with a many-to-one interference channel. Using lattices, joint maximum-likelihood decoding of the desired signal and the sum of the interference signals is used, and the union bound of the error probability for user 1 is derived, in terms of the theta series. Later, a symmetric interference channel is studied. Jafar built a scheme for every level of interference, where interference was aligned and could be cancelled. In this thesis, Barnes-Wall lattices are used since they have a similar structure to the scheme proposed by Jafar, and it is shown to be possible to improve the performance of the technique using codes constructed with Barnes-Wall lattices. Finally, previous work has found the generalized degrees of freedom for a two-user symmetric interference channel using random codes. Here, we obtain the generalized degrees of freedom for that channel setting using lattice Gaussian distribution.Open Acces
Compute-and-Forward: Harnessing Interference through Structured Codes
Interference is usually viewed as an obstacle to communication in wireless
networks. This paper proposes a new strategy, compute-and-forward, that
exploits interference to obtain significantly higher rates between users in a
network. The key idea is that relays should decode linear functions of
transmitted messages according to their observed channel coefficients rather
than ignoring the interference as noise. After decoding these linear equations,
the relays simply send them towards the destinations, which given enough
equations, can recover their desired messages. The underlying codes are based
on nested lattices whose algebraic structure ensures that integer combinations
of codewords can be decoded reliably. Encoders map messages from a finite field
to a lattice and decoders recover equations of lattice points which are then
mapped back to equations over the finite field. This scheme is applicable even
if the transmitters lack channel state information.Comment: IEEE Trans. Info Theory, to appear. 23 pages, 13 figure
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
Secure Degrees of Freedom for Gaussian Channels with Interference: Structured Codes Outperform Gaussian Signaling
In this work, we prove that a positive secure degree of freedom is achievable
for a large class of Gaussian channels as long as the channel is not degraded
and the channel is fully connected. This class includes the MAC wire-tap
channel, the 2-user interference channel with confidential messages, the 2-user
interference channel with an external eavesdropper. Best known achievable
schemes to date for these channels use Gaussian signaling. In this work, we
show that structured codes outperform Gaussian random codes at high SNR when
channel gains are real numbers.Comment: 6 pages, Submitted to IEEE Globecom, March 200
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