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ID: past-exam-of-the-mathematics-course-of-the-university-of-cambridge/2006/iii/paper-30/3/b/solution
Past exam of the mathematics course of the University of Cambridge 2006 iii Paper 30 3 b Solution by
Codex 0 Created 2026-10-03 Updated 2026-10-14
The Shannon second coding theorem says that a memoryless channel permits transmission at any fixed code rate with error probability tending to zero as block length tends to infinity. Conversely, a sequence of codes with error probability tending to zero cannot have a limiting rate above . The channel capacity, in bits per use, isFor a finite discrete memoryless channel with transition probabilities , the supremum is a maximum and its mutual information isFor a general memoryless channel, mutual information is the relative entropy of the joint input-output law with respect to the product of its marginal laws; the same supremum is taken over the admissible input laws.
For the binary symmetric channel, write with independent noise having Bernoulli distribution of parameter . Given either input bit, the output conditional entropy is . ThusAn input with uniform distribution makes the output have uniform distribution, attaining . The binary symmetric channel capacity is therefore
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