Publication

Fountain Capacity

Emre Telatar
2006
Conference Papers

Abstract

Fountain codes have been successfully employed for reliable and efficient transmission of information via erasure channels with unknown erasure rates. This paper introduces the notion of fountain capacity for arbitrary channels, and shows that it is equal to the conventional Shannon capacity for stationary memoryless channels. In contrast, when the channel is not stationary or has memory, Shannon capacity and fountain capacity need not be equal.

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Emre Telatar
2006
Conference Papers

Abstract

Official source

Related concepts (32)

Channel capacity

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.

Noisy-channel coding theorem

In information theory, the noisy-channel coding theorem (sometimes Shannon's theorem or Shannon's limit), establishes that for any given degree of noise contamination of a communication channel, it is possible to communicate discrete data (digital information) nearly error-free up to a computable maximum rate through the channel. This result was presented by Claude Shannon in 1948 and was based in part on earlier work and ideas of Harry Nyquist and Ralph Hartley.

Erasure code

In coding theory, an erasure code is a forward error correction (FEC) code under the assumption of bit erasures (rather than bit errors), which transforms a message of k symbols into a longer message (code word) with n symbols such that the original message can be recovered from a subset of the n symbols. The fraction r = k/n is called the code rate. The fraction k’/k, where k’ denotes the number of symbols required for recovery, is called reception efficiency.

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