Lozano Solsona, AngelTulino, Antonia M.Verdú, Sergio2012-01-192012-01-192006Lozano A, Tulino A M, Verdu S. Optimum power allocation for parallel Gaussian channels with arbitrary input distributions. IEEE Transactions on Information Theory. 2006; 52(7): 3033-3051. DOI 10.1109/TIT.2006.8762200018-9448http://hdl.handle.net/10230/16123The mutual information of independent parallel Gaussian-noise channels is maximized, under an average power constraint, by independent Gaussian inputs whose power is allocated according to the waterfilling policy. In practice, discrete signalling constellations with limited peak-to-average ratios (m-PSK, m-QAM, etc) are used in lieu of the ideal Gaussian /nsignals. This paper gives the power allocation policy that maximizes the mutual information /nover parallel channels with arbitrary input distributions. Such policy admits a graphical interpretation, referred to as mercury/waterfilling, which generalizes the waterfilling solution and allows retaining some of its intuition. The relationship between mutual information of Gaussian channels and nonlinear minimum mean-square error proves key to solving the power allocation problem.application/pdfeng© 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works./nThe final published article can be found at http://dx.doi.org/10.1109/TIT.2006.876220Ràdio -- InterferènciesTractament del senyalOptimum power allocation for parallel Gaussian channels with arbitrary input distributionsinfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1109/TIT.2006.876220Gaussian ChannelsPower AllocationWaterfillingChannel CapacityMutual InformationMMSEinfo:eu-repo/semantics/openAccess