Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Concept
Channel capacity
Summary
Channel capacity, in electrical engineering, computer science, and information theory, is the tight upper bound on the rate at which information can be reliably transmitted over a communication channel.
Following the terms of the noisy-channel coding theorem, the channel capacity of a given channel is the highest information rate (in units of information per unit time) that can be achieved with arbitrarily small error probability.
Information theory, developed by Claude E. Shannon in 1948, defines the notion of channel capacity and provides a mathematical model by which it may be computed. The key result states that the capacity of the channel, as defined above, is given by the maximum of the mutual information between the input and output of the channel, where the maximization is with respect to the input distribution.
The notion of channel capacity has been central to the development of modern wireline and wireless communication systems, with the advent of novel error correction coding mechanisms that have resulted in achieving performance very close to the limits promised by channel capacity.
The basic mathematical model for a communication system is the following:
where:
is the message to be transmitted;
is the channel input symbol ( is a sequence of symbols) taken in an alphabet ;
is the channel output symbol ( is a sequence of symbols) taken in an alphabet ;
is the estimate of the transmitted message;
is the encoding function for a block of length ;
is the noisy channel, which is modeled by a conditional probability distribution; and,
is the decoding function for a block of length .
Let and be modeled as random variables. Furthermore, let be the conditional probability distribution function of given , which is an inherent fixed property of the communication channel. Then the choice of the marginal distribution completely determines the joint distribution due to the identity
which, in turn, induces a mutual information . The channel capacity is defined as
where the supremum is taken over all possible choices of .
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.