Generalized Mercury/Waterfilling for Multiple-Input Multiple-Output Channels
نویسندگان
چکیده
We determine the power-allocation policy that maximizes the mutual information for general multiple-input multipleoutput Gaussian channels with arbitrary input distributions, by capitalizing on the recent relationship between mutual information and minimum mean squared error (MMSE). In this context, we put forth a novel interpretation of the optimal powerallocation procedure that generalizes the mercury/waterfilling algorithm, previously proposed for parallel non-interfering channels. In this generalization the mercury level accounts for the suboptimal (non-Gaussian) input distribution and the interferences between inputs.
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