697 research outputs found
Interference Alignment for Cognitive Radio Communications and Networks: A Survey
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe
On the Feasibility of Linear Interference Alignment for MIMO Interference Broadcast Channels with Constant Coefficients
In this paper, we analyze the feasibility of linear interference alignment
(IA) for multi-input-multi-output (MIMO) interference broadcast channel
(MIMO-IBC) with constant coefficients. We pose and prove the necessary
conditions of linear IA feasibility for general MIMO-IBC. Except for the proper
condition, we find another necessary condition to ensure a kind of irreducible
interference to be eliminated. We then prove the necessary and sufficient
conditions for a special class of MIMO-IBC, where the numbers of antennas are
divisible by the number of data streams per user. Since finding an invertible
Jacobian matrix is crucial for the sufficiency proof, we first analyze the
impact of sparse structure and repeated structure of the Jacobian matrix.
Considering that for the MIMO-IBC the sub-matrices of the Jacobian matrix
corresponding to the transmit and receive matrices have different repeated
structure, we find an invertible Jacobian matrix by constructing the two
sub-matrices separately. We show that for the MIMO-IBC where each user has one
desired data stream, a proper system is feasible. For symmetric MIMO-IBC, we
provide proper but infeasible region of antenna configurations by analyzing the
difference between the necessary conditions and the sufficient conditions of
linear IA feasibility.Comment: 14 pages, 3 figures, accepted by IEEE Trans. on Signal Processin
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
Interference Alignment with Limited Feedback on Two-cell Interfering Two-User MIMO-MAC
In this paper, we consider a two-cell interfering two-user multiple-input
multiple-output multiple access channel (MIMO-MAC) with limited feedback. We
first investigate the multiplexing gain of such channel when users have perfect
channel state information at transmitter (CSIT) by exploiting an interference
alignment scheme. In addition, we propose a feedback framework for the
interference alignment in the limited feedback system. On the basis of the
proposed feedback framework, we analyze the rate gap loss and it is shown that
in order to keep the same multiplexing gain with the case of perfect CSIT, the
number of feedback bits per receiver scales as , where and denote the number of
transmit antennas and a constant, respectively. Throughout the simulation
results, it is shown that the sum-rate performance coincides with the derived
results.Comment: 6 pages, 2 figures, Submitted ICC 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
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