An Algebraic, Analytic, and Algorithmic Investigation on the Capacity and Capacity-Achieving Input Probability Distributions of Finite-Input– Finite-Output Discrete Memoryless Channels
Xue-Bin Liang
Dept. of Electr. & Comput. Eng., Louisiana State Univ., Baton Rouge, LA;
This paper appears in: Information Theory, IEEE Transactions on
Publication Date: March 2008
Volume: 54,
Issue: 3
On page(s): 1003-1023
ISSN: 0018-9448
INSPEC Accession Number: 10145841
Digital Object Identifier: 10.1109/TIT.2007.915703
Current Version Published: 2008-02-22
Abstract
In this paper, we investigate the capacity and capacity-achieving input probability distributions (IPDs) of finite-input-finite-output discrete memoryless channels (DMCs). In the general respect, we establish a novel and simple characterization for the capacity-achieving IPDs of a DMC, which is equivalent to the conventional Kuhn-Tucker conditions. We then prove a conjecture of Majani and Rumsey, which claims that every probability component of each capacity-achieving IPD of a DMC with positive capacity is less than 1-e-1, where e = 2.71828182... is the base of natural logarithms. It remains an open problem whether there exists an explicit closed-form solution for the capacity and capacity-achieving IPDs of a general finite-input-finite-output DMC, except for the two-input-two-output DMC. In the algebraic respect, we demonstrate that there does not, in general, exist an algebraic solution for the capacity-achieving IPDs of an m-input-n-output DMC for any m ges 2 . and any n ges 3. In the analytic respect, however, we can obtain an explicit closed-form analytic solution, represented as an infinite series, for the capacity-achieving IPD of a two-input-three-output DMC. We also provide a formula for the average capacity of weakly symmetric DMCs and show that the average capacity in nats per channel use of the n-input-m-output weakly symmetric DMCs increases for n ges 2 but has a finite limit of 1 - gamma as n rarr infin, where gamma = 0.57721566... is Euler's constant. In the algorithmic respect, the convergence of the Arimoto-Blahut algorithm is proved in a direct and elementary way. A new and simple iterative algorithm for calculating a capacity-achieving IPD is then proposed, which is provably convergent for all DMCs with positive transition probabilities. Finally, the characterization and determination of the set of all capacity-achieving IPDs of a DMC are addressed.
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