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Optimization under multiple linear constraints is important for practical systems with individual power constraints, per-antenna power constraints, and/or interference constraints as in cognitive radios. While for single-user multiple-input multiple-output (MIMO) channel transmitter optimization, no one uses general purpose convex programming because water-filling is optimal and much simpler, it is...
The algorithms in this paper exploit optimal input structure in interference networks and is a major advance from the state-of-the-art. Optimization under multiple linear constraints is important for interference networks with individual power constraints, per-antenna power constraints, and/or interference constraints as in cognitive radios. While for single-user MIMO channel transmitter optimization,...
It is well known that in general, the traditional water-filling is far from optimal in networks. We recently found the long-sought network version of water-filling named polite water-filling that is optimal for a large class of MIMO networks called B-MAC networks, of which interference Tree (iTree) networks is a subset whose interference graphs have no directional loop. iTree networks is a natural...
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