2,756 research outputs found
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
When Does an Ensemble of Matrices with Randomly Scaled Rows Lose Rank?
We consider the problem of determining rank loss conditions for a
concatenation of full-rank matrices, such that each row of the composing
matrices is scaled by a random coefficient. This problem has applications in
wireless interference management and recommendation systems. We determine
necessary and sufficient conditions for the design of each matrix, such that
the random ensemble will almost surely lose rank by a certain amount. The
result is proved by converting the problem to determining rank loss conditions
for the union of some specific matroids, and then using tools from matroid and
graph theories to derive the necessary and sufficient conditions. As an
application, we discuss how this result can be applied to the problem of
topological interference management, and characterize the linear symmetric
degrees of freedom for a class of network topologies.Comment: submitted to IEEE Transactions on Information Theory; shorter version
to appear at IEEE International Symposium on Information Theory (ISIT 2015
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