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It connects Hartley's result with Shannon's channel capacity theorem in a form that is equivalent to specifying the M in Hartley's line rate formula in terms of a signal-to-noise ratio, but achieving reliability through error-correction coding rather than through reliably distinguishable pulse levels.
The channel capacity can be calculated from the physical properties of a channel; for a band-limited channel with Gaussian noise, using the Shannon–Hartley theorem. Simple schemes such as "send the message 3 times and use a best 2 out of 3 voting scheme if the copies differ" are inefficient error-correction methods, unable to asymptotically ...
This result is known as the Shannon–Hartley theorem. [11] When the SNR is large (SNR ≫ 0 dB), the capacity ¯ is logarithmic in power and approximately linear in bandwidth. This is called the bandwidth-limited regime.
This relationship is described by the Shannon–Hartley theorem, which is a fundamental law of information theory. ... (PDF) from the original on 2022-10-09 ...
the mutual information, and the channel capacity of a noisy channel, including the promise of perfect loss-free communication given by the noisy-channel coding theorem; the practical result of the Shannon–Hartley law for the channel capacity of a Gaussian channel; as well as; the bit—a new way of seeing the most fundamental unit of information.
Download as PDF; Printable version; ... Shannon's source coding theorem; Channel capacity; Noisy-channel coding theorem; Shannon–Hartley theorem;
Download as PDF; Printable version; In other projects Wikidata item; Appearance. move to sidebar hide. Help ... Shannon–Hartley theorem; Shannon's source coding theorem
In the famous Shannon–Hartley theorem, the C/N ratio is equivalent to the S/N ratio. The C/N ratio resembles the carrier-to-interference ratio (C/I, CIR), and the carrier-to-noise-and-interference ratio, C/(N+I) or CNIR. C/N estimators are needed to optimize the receiver performance. [1]