Abstract

Important problems exist in the field of communications theory whose solution is in the form of an expectation of a function of a random variable. Often it is not computationally feasible to evaluate these moments exactly. This paper presents a geometric bounding technique that yields tight upper and lower bounds to generalized moments of a broad class of random variables. This technique produces excellent results for these communications theory problems.

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