Journal: Advances in Mathematics of Communications
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American Institute of Mathematical Sciences
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- Capacity of random channels with large alphabetsItem type: Journal Article
Advances in Mathematics of CommunicationsSutter, Tobias; Sutter, David; Lygeros, John (2017)We consider discrete memoryless channels with input alphabet size n and output alphabet size m, where m = [γn] for some constant γ > 0. The channel transition matrix consists of entries that, before being normalized, are independent and identically distributed nonnegative random variables V and such that E[(V log V )2] < ∞. We prove that in the limit as n → ∞ the capacity of such a channel converges to E[(V]=E[V] almost surely and in L2, where Ent[(V) := E[V log V] - E[V] log E[V ] denotes the entropy of V. We further show that, under slightly different model assumptions, the capacity of these random channels converges to this asymptotic value exponentially in n. Finally, we present an application in the context of Bayesian optimal experiment design. © 2017 AIMS.
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