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Gaussian Channel

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Channel CapacityChannel Coding Theorem+1 more→→MIMO Capacity
Gaussian channel AWGN Shannon-Hartley SNR bandwidth

Core Idea

The additive white Gaussian noise (AWGN) channel models a continuous-valued channel where the received signal Y = X + Z, with Z ~ N(0, N) independent of the input X, and the input has a power constraint E[X2] <= P. Its capacity is C = (1/2) log2(1 + P/N) bits per channel use — the Shannon-Hartley formula. The capacity-achieving input distribution is Gaussian: X ~ N(0, P). Combined with the bandwidth theorem, this gives C = W log2(1 + P/(NW)) bits per second for bandwidth W, establishing the fundamental tradeoff between bandwidth, power, and data rate that governs all modern wireless and wired communication.

Explainer

The additive white Gaussian noise (AWGN) channel is the most important continuous channel model in information theory. It models any communication system where the dominant impairment is thermal noise: Y = X + Z, where X is the transmitted signal, Z ~ N(0, N) is Gaussian noise, and E[X2] <= P constrains the transmit power. The capacity of this channel — the Shannon-Hartley formula — is one of the most important equations in engineering.

The capacity derivation uses differential entropy. I(X;Y) = h(Y) - h(Y|X). Since Y|X = X + Z and Z is independent of X, h(Y|X) = h(Z) = (1/2) log2(2*pi*e*N), which is fixed. To maximize I(X;Y), we maximize h(Y). The variance of Y = X + Z is Var(X) + N <= P + N. Among all distributions with a given variance, the Gaussian maximizes differential entropy. So h(Y) <= (1/2) log2(2*pi*e*(P+N)), with equality when X ~ N(0, P). The capacity is C = (1/2) log2(2*pi*e*(P+N)) - (1/2) log2(2*pi*e*N) = (1/2) log2(1 + P/N).

The bandwidth extension connects to real-world systems. A band-limited channel of bandwidth W Hz can carry 2W independent real-valued samples per second (Nyquist's theorem). If the noise power spectral density is N_0/2, the total noise power in bandwidth W is N = N_0*W. With total signal power P, the capacity in bits per second is C = W * log2(1 + P/(N_0*W)). This formula captures the fundamental bandwidth-power tradeoff: you can increase data rate by using more bandwidth (but with diminishing returns) or more power (with logarithmic returns). The limit as W goes to infinity with fixed P is C = P/(N_0 * ln 2) — Shannon's ultimate limit, determined by power alone.

Modern communication systems (4G LTE, 5G NR, Wi-Fi 6/7, satellite links) are designed with this formula as the benchmark. The gap between a system's actual throughput and the Shannon-Hartley capacity quantifies how much room for improvement exists. Turbo codes and LDPC codes operate within 0.1 dB of the Gaussian channel capacity, a remarkable engineering achievement that took nearly 50 years after Shannon's theorem to attain.

Practice Questions 3 questions

Prerequisite Chain

Understanding Zero → The Number Zero → Counting to Five → Counting to 10 → Counting to 20 → Counting a Set of Objects Up to 20 → Cardinality: The Last Number Counted → Matching Numerals to Quantities → Subitizing Small Quantities → Addition Within 10 → Number Bonds to 10 → Addition Within 20 → Doubles and Near Doubles → Doubles Facts Within 10 → Near Doubles Facts Within 20 → Mental Math Strategies for Addition → Mental Math: Adding and Subtracting Tens → Addition Within 100 → Repeated Addition as Multiplication → Multiplication as Equal Groups → Multiplication: Arrays → Basic Multiplication Facts (0s, 1s, 2s, 5s, 10s) → Multiplication Facts Within 100 → Division as Equal Sharing → Division as Grouping (Measurement Division) → Division: Grouping (Repeated Subtraction) Model → Division: Fair Sharing Model → Division as Equal Sharing → Division as Grouping → Basic Division Facts → Division Facts Within 100 → Multiplication and Division Fact Families → Relationship Between Multiplication and Division → Division Facts as Inverse of Multiplication → Remainders and Quotients in Division → Division Word Problems → Multi-Step Word Problems → Solving Multi-Step Word Problems → Multiplication Word Problems → Division Word Problems → Introduction to Long Division → Factors and Multiples → Prime and Composite Numbers → Equivalent Fractions → Relating Fractions and Decimals → Decimal Place Value → Integers and the Number Line → Comparing and Ordering Integers → Absolute Value → Adding Integers → Subtracting Integers → Multiplying Integers → Dividing Integers → Unit Rates → Proportions → Percent Concept → Converting Between Fractions, Decimals, and Percents → Operations with Rational Numbers → Two-Step Equations → Solving Multi-Step Equations → Equations with Variables on Both Sides → Angle Pairs: Complementary, Supplementary, and Vertical → Parallel Lines and Transversals → Corresponding Angles → Alternate Interior Angles → Triangle Angle Sum Theorem → Exterior Angle Theorem → Triangle Inequality Theorem → Similar Triangles: AA Similarity → Similar Triangles: SSS and SAS Similarity → Proportions in Similar Triangles → Right Triangle Trigonometry Introduction → Sine, Cosine, and Tangent Ratios → Trigonometric Ratios Review → Radian Measure → Converting Between Degrees and Radians → The Unit Circle → Graphing Sine and Cosine → Graphing Tangent and Reciprocal Trigonometric Functions → Derivatives of Trigonometric Functions → Antiderivatives → Indefinite Integrals → Basic Integration Rules → Riemann Sums → Definite Integral Definition → Probability Density Functions and Continuous Distributions → Cumulative Distribution Functions → Continuous Random Variables → Probability Density Functions → Expected Value → Weak Law of Large Numbers → Probability Axioms and Rules → Conditional Probability → Law of Total Probability → Bayes' Theorem → Joint and Conditional Entropy → Mutual Information → Channel Capacity → Binary Symmetric Channel → Channel Coding Theorem → Gaussian Channel

Longest path: 101 steps · 448 total prerequisite topics

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