523 research outputs found
Asymptotic Estimates in Information Theory with Non-Vanishing Error Probabilities
This monograph presents a unified treatment of single- and multi-user
problems in Shannon's information theory where we depart from the requirement
that the error probability decays asymptotically in the blocklength. Instead,
the error probabilities for various problems are bounded above by a
non-vanishing constant and the spotlight is shone on achievable coding rates as
functions of the growing blocklengths. This represents the study of asymptotic
estimates with non-vanishing error probabilities.
In Part I, after reviewing the fundamentals of information theory, we discuss
Strassen's seminal result for binary hypothesis testing where the type-I error
probability is non-vanishing and the rate of decay of the type-II error
probability with growing number of independent observations is characterized.
In Part II, we use this basic hypothesis testing result to develop second- and
sometimes, even third-order asymptotic expansions for point-to-point
communication. Finally in Part III, we consider network information theory
problems for which the second-order asymptotics are known. These problems
include some classes of channels with random state, the multiple-encoder
distributed lossless source coding (Slepian-Wolf) problem and special cases of
the Gaussian interference and multiple-access channels. Finally, we discuss
avenues for further research.Comment: Further comments welcom
Secure Multiplex Coding with Dependent and Non-Uniform Multiple Messages
The secure multiplex coding (SMC) is a technique to remove rate loss in the
coding for wire-tap channels and broadcast channels with confidential messages
caused by the inclusion of random bits into transmitted signals. SMC replaces
the random bits by other meaningful secret messages, and a collection of secret
messages serves as the random bits to hide the rest of messages. In the
previous researches, multiple secret messages were assumed to have independent
and uniform distributions, which is difficult to be ensured in practice. We
remove this restrictive assumption by a generalization of the channel
resolvability technique.
We also give practical construction techniques for SMC by using an arbitrary
given error-correcting code as an ingredient, and channel-universal coding of
SMC. By using the same principle as the channel-universal SMC, we give coding
for the broadcast channel with confidential messages universal to both channel
and source distributions.Comment: We made several changes to improve the presentatio
On the Combinatorial Version of the Slepian-Wolf Problem
We study the following combinatorial version of the Slepian-Wolf coding
scheme. Two isolated Senders are given binary strings and respectively;
the length of each string is equal to , and the Hamming distance between the
strings is at most . The Senders compress their strings and
communicate the results to the Receiver. Then the Receiver must reconstruct
both strings and . The aim is to minimise the lengths of the transmitted
messages.
For an asymmetric variant of this problem (where one of the Senders transmits
the input string to the Receiver without compression) with deterministic
encoding a nontrivial lower bound was found by A.Orlitsky and K.Viswanathany.
In our paper we prove a new lower bound for the schemes with syndrome coding,
where at least one of the Senders uses linear encoding of the input string.
For the combinatorial Slepian-Wolf problem with randomized encoding the
theoretical optimum of communication complexity was recently found by the first
author, though effective protocols with optimal lengths of messages remained
unknown. We close this gap and present a polynomial time randomized protocol
that achieves the optimal communication complexity.Comment: 20 pages, 14 figures. Accepted to IEEE Transactions on Information
Theory (June 2018
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