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Sum-Set Inequalities From Aligned Image Sets: Instruments for Robust GDoF Bounds | IEEE Journals & Magazine | IEEE Xplore

Sum-Set Inequalities From Aligned Image Sets: Instruments for Robust GDoF Bounds


Abstract:

We present sum-set inequalities specialized to the generalized degrees of freedom (GDoF) framework. These are information theoretic lower bounds on the entropy of bounded...Show More

Abstract:

We present sum-set inequalities specialized to the generalized degrees of freedom (GDoF) framework. These are information theoretic lower bounds on the entropy of bounded density linear combinations of discrete, power-limited dependent random variables in terms of the joint entropies of arbitrary linear combinations of new random variables that are obtained by power level partitioning of the original random variables. These bounds generalize the aligned image sets approach, and are useful instruments to obtain GDoF characterizations for wireless networks, especially with multiple antenna nodes, subject to arbitrary channel strength and channel uncertainty levels. To demonstrate the utility of these bounds, we consider various examples of interference and broadcast channels for which we obtain tight GDoF characterizations with the aid of sum-set inequalities.
Published in: IEEE Transactions on Information Theory ( Volume: 66, Issue: 10, October 2020)
Page(s): 6458 - 6487
Date of Publication: 22 June 2020

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