चैनल-क्षमता इसके अंग्रेजी अर्थ का उदाहरण

The protocol of superdense coding has been actualized in several experiments using different systems to varying levels of channel capacity and fidelities.

In 2004, trapped beryllium 9 ions were used in a maximally entangled state to achieve a channel capacity of 1.

In 2017, a channel capacity of 1.

High dimensional ququarts (states formed in photon pairs by non-degenerate spontaneous parametric down-conversion) were used to reach a channel capacity of 2.

In smaller markets, especially those with cable systems whose headends had limited channel capacity, the channel was only made available on a gametime basis as a pay-per-view option and often limited telecast to only Stanley Cup playoff games.

However, by 1985, WPTV had been dropped from most Miami cable systems to make way for new cable channels (partly due to limited headend channel capacity), resulting in some NBC programs that were preempted by WSVN being unavailable to some viewers.

Repetition codes are one of the few known codes whose code rate can be automatically adjusted to varying channel capacity, by sending more or less parity information as required to overcome the channel noise, and it is the only such code known for non-erasure channels.

The Shannon theorem states that given a noisy channel with channel capacity C and information transmitted at a rate R, then if R there exist codes that allow the probability of error at the receiver to be made arbitrarily small.

So, information cannot be guaranteed to be transmitted reliably across a channel at rates beyond the channel capacity.

The channel capacity C can be calculated from the physical properties of a channel; for a band-limited channel with Gaussian noise, using the Shannon–Hartley theorem.

For every discrete memoryless channel, the channel capacity is defined in terms of the mutual information I(X; Y),.

Both types of proofs make use of a random coding argument where the codebook used across a channel is randomly constructed - this serves to make the analysis simpler while still proving the existence of a code satisfying a desired low probability of error at any data rate below the channel capacity.

Then the channel capacity is given by.