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Alternating minimization and steepest descent are commonly used strategies to obtain interference alignment (IA) solutions in the -user multiple-input multiple-output (MIMO) interference channel (IC). Although these algorithms are shown to converge monotonically, they experience a poor convergence rate, requiring an enormous amount of iterations which substantially increases with the size of the...
Alternating minimization algorithms are typically used to find interference alignment (IA) solutions for multiple-input multiple-output (MIMO) interference channels with more than K=3 users. For these scenarios many IA solutions exit, and the initial point determines which one is obtained upon convergence. In this paper, we propose a new iterative algorithm that aims at finding the IA solution that...
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