Noisy-channel coding theorem: Difference between revisions

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Both types of proofs make use of a random coding argument where the codebook used across a channel is randomly constructed - this serves to reduce computational complexity while still proving the existence of a code satisfying a desired low probability of error at any data rate below the [[Channel capacity]].
 
By an AEP-related argument, given a channel, length n strings of source symbols <math>X_1^{n}</math>, and length n strings of channel outputs <math>Y_1^{n}</math>, we can define a ''jointly typical set'' by the following:
 
<math>A_\epsilon^{(n)} = \{(x^n, y^n) \in \mathcal X^n \times \mathcal Y^n </math>