DocumentCode
3120655
Title
Interference alignment: From degrees-of-freedom to constant-gap capacity approximations
Author
Niesen, Urs ; Maddah-Ali, Mohammad A.
Author_Institution
Bell Labs., Alcatel-Lucent, Murray Hill, NJ, USA
fYear
2012
fDate
1-6 July 2012
Firstpage
2077
Lastpage
2081
Abstract
Interference alignment is a key technique for communication scenarios with multiple interfering links. In several such scenarios, interference alignment was used to characterize the degrees-of-freedom of the channel. However, these degrees-of-freedom capacity approximations are often too weak to make accurate predictions about the behavior of channel capacity at finite signal-to-noise ratios. The aim of this paper is to significantly strengthen these results by showing that interference alignment can be used to characterize capacity to within a constant gap. We focus on real time-invariant frequency-flat X-channels, for which only the degrees-of-freedom are known. We propose a new communication scheme and show that it achieves the capacity of the Gaussian X-channel to within a constant gap. To aid in this process, we develop a novel deterministic channel model, admitting a wider range of achievable schemes that can be translated to the Gaussian channel. For this deterministic model, we find an approximately optimal communication scheme. We then translate this scheme for the deterministic channel to the original Gaussian X-channel and show that it achieves capacity to within a constant gap. This is the first constant-gap result for a fully-connected network requiring interference alignment.
Keywords
Gaussian channels; radiofrequency interference; Gaussian X-channel; Gaussian channel; channel capacity behavior; constant-gap capacity approximations; degrees-of-freedom capacity approximations; deterministic channel model; finite signal-to-noise ratios; interference alignment; multiple interfering links; optimal communication scheme; time-invariant frequency-flat X-channels; Approximation methods; Channel models; Interference channels; Receivers; Transmitters; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory Proceedings (ISIT), 2012 IEEE International Symposium on
Conference_Location
Cambridge, MA
ISSN
2157-8095
Print_ISBN
978-1-4673-2580-6
Electronic_ISBN
2157-8095
Type
conf
DOI
10.1109/ISIT.2012.6283727
Filename
6283727
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