Chapter 4 / 4.18 / 4.18.2

4.18.2 What Is Shannon's Information Capacity Theorem?

Discover Claude Shannon's revolutionary theorem that established the maximum achievable data rate of a noisy channel. Learn what channel capacity means, why the Shannon limit exists, and how modern coding systems approach theoretical performance limits.

1. Who Was Claude Shannon?
2. What Is Channel Capacity?
3. Why is it called Shannon–Hartley equation?
4. Why Not Just Call It Shannon's Equation?
5. Why Does Noise Limit Communication?
6. What Does the Equation Tell Us?
7. Why Is the Logarithmic Relationship Important?
8. What Is Signal-to-Noise Ratio?
9. What Is the Shannon Limit?
10. Does Shannon's Theorem Describe a Real System?
11. What Is Spectral Efficiency?
12. Why Is Spectral Efficiency Important?
13. What Is the Relationship Between Capacity and Eb/N₀?
14. What Is Special About −1.59 dB?
15. What Are Power-Limited Systems?
16. What Are Bandwidth-Limited Systems?
17. Can Capacity Be Increased Indefinitely?
18. How Close Do Modern Systems Come to Capacity?
19. What Is the Importance of Shannon's Theorem?
20. Where Is Shannon's Theorem Used?
21. Why Is Shannon's Information Capacity Theorem Important?

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