Interference alignment via alternating minimization

By Steven W. Peters, Robert W. Heath. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2009

455 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

On the Degrees of Freedom Achievable Through Interference Alignment in a MIMO Interference Channel (2011, result): “nds in Theorem 1 and Theorem 2 are satisﬁed, suggesting the interference alignm ent is achievable. We plot the sum-rate results of the Distributed Interference Alignment (DIA) algorithm [3] (see also [7]). The “Predicted Slope” line has the slope corresponding to the DoF in the system and it starts ”
Interference Alignment: A New Look at Signal Dimensions in a Communication Network (2011, methodology): “Reference [116] presents an alternating minimization approach that does not explicitly assume channel reciprocity, but is algorithmically identical to the distributed interference alignment algorithm of [48].”
Cooperative Algorithms for MIMO Interference Channels (2010, methodology): “We therefore take the standard approach [13], [15] and focus on the transmission of a single vector symbol s k from transmitter k ∈ { 1 , . . . , K } , neglecting any time dependency.”
Optimal Resource Allocation for MIMO Ad Hoc Cognitive Radio Networks (2008, background): “Recent advances in the degrees-of-freedom characterization of MIMO interference channels (ICs) motivated development of optimization algorithms based on interference alignment [9], [20].”
What Will 5G Be? (2014, unknown): “[18] S.”