New Results on the DMC Capacity and Renyi's Divergence
Yi Janet Lu

TL;DR
This paper investigates the analytical computation of channel capacity for discrete memoryless channels using the Blahut-Arimoto algorithm and recent methods, and explores the relationship between Renyi's divergence and generalized channel capacity.
Contribution
It provides complexity analysis of capacity approximation algorithms and examines the connection between Renyi's divergence and channel capacity in a new setting.
Findings
Blahut-Arimoto algorithm complexity: O(MN^2 log N / ε)
Recent methods complexity: O(M^2 N √log N / ε)
Relation between Renyi's divergence and generalized capacity studied
Abstract
This work is part of a project "Walsh Spectrum Analysis and the Cryptographic Applications". The project initiates the study of finding the largest (and/or significantly large) Walsh coefficients as well as the index positions of an unknown distribution by random sampling. This proposed problem has great significance in cryptography and communications. In early 2015, Yi JANET Lu first constructed novel imaginary channel transition matrices and introduced Shannon's channel coding problem to statistical cryptanalysis. For the first time, the channel capacity results of well-chosen transition matrices, which might be impossible to calculate traditionally, become of hottest research focus. For a few Discrete Memoryless Channels (DMCs), it is known that the capacity can be computed analytically; in general, there is no closed-form solution. This work is concerned with analytical results of…
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Taxonomy
TopicsCellular Automata and Applications · Computability, Logic, AI Algorithms · DNA and Biological Computing
