Corpus ID: 5747983

A Mathematical Theory of Communication

  title={A Mathematical Theory of Communication},
  author={Jin Shin and Sang Joon Kim},
This paper opened the new area the information theory. Before this paper, most people believed that the only way to make the error probability of transmission as small as desired is to reduce the data rate (such as a long repetition scheme). However, surprisingly this paper revealed that it does not need to reduce the data rate for achieving that much of small errors. It proved that we can get some positive data rate that has the same small error probability and also there is an upper bound of… Expand
The birthday problem and zero-error list codes
This paper studies the performance of randomly generated codebooks over discrete memoryless channels under a zero-error constraint and leads to an information-theoretic formulation of the birthday problem, which is concerned with the probability that in a given population, a fixed number of people have the same birthday. Expand
Error Probability Analysis of Binary Asymmetric Channels
In his world-famous paper of 1948, Shannon defined channel capacity as the ultimate rate at which information can be transmitted over a communication channel with an error probability that willExpand
Fundamental Limits of Communication With Low Probability of Detection
This paper considers the problem of communication over a discrete memoryless channel (DMC) or an additive white Gaussian noise (AWGN) channel subject to the constraint that the probability that anExpand
Limits of low-probability-of-detection communication over a discrete memoryless channel
This paper considers the problem of communication over a discrete memoryless channel subject to the constraint that the probability that an adversary who observes the channel outputs can detect theExpand
Information Theory Tutorial Communication over Channels with memory
A general capacity formula C = sup X I(X; Y), which is correct for arbitrary single-user channels without feedback, is introduced in this tutorial. This new capacity formula is obtained by using aExpand
Channel Coding
  • A. Ahrens
  • Video Coding for Wireless Communication Systems
  • 2018
Prior to Shannon results, it was belived that the error proba bility of the channel communication in Figure 1, grows asR grows, whereR is the rate transmitted through the channel, i.e., the number ofExpand
Uncomputability of the generalized capacity
It is shown that there is no equivalent to the Blahut-Arimoto algorithm for computing the generalized capacity of a channel and that such an algorithm can not exist. Expand
On the Power of Feedback in Interactive Channels
In classical information theory it is well-known that feedback does not improve the channel capacity. We demonstrate that this is not the case in the interactive setting by developing a new codingExpand
On Bounds for E-Capacity of DMC
  • E. Haroutunian
  • Mathematics, Computer Science
  • IEEE Trans. Inf. Theory
  • 2007
This paper summarizes and revises the results of previous hardly accessible publications of the author and summarizes the method of types and graph decomposition for E-capacity of discrete memoryless channel (DMC). Expand
Information-theoretic aspects of optical communications
New upper and lower bounds on the amount of classical information that can be transmitted through a single use of a quantum channel, under a constraint on the average error probability are proved. Expand