Interference alignment (IA) is a cooperative transmission strategy that can mitigate the effects of interference in distributed wireless networks. As its name suggests, the idea of alignment is to structure interference such that multiple interfering signals overlap at the receiver. The alignment property enables efficient interference cancellation. This article provides a brief review of the concept of interference alignment, with a focus on linear precoding-based IA strategies for the multiple-input multiple-output (MIMO) interference channel, and surveys some of the authors' recent results on the subject, with a special focus on making IA more practical. The key concepts discussed range from algorithmic improvements to early IA solutions, to managing the overhead associated with user cooperation. The article highlights some active areas, and future directions, in IA research.
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