What the syllabus asks you to cover
Random Signal and processes, White Noise, Thermal Noise, Bandlimited White Noise, the PSDF and AC function of White Noise.
Start here for the core ideas. A dedicated GitBook topic page was not available; this original guide is introductory. Use the syllabus checklist and references below to study the remaining details.
Treat noise statistically
A random process describes a family of possible waveforms. Mean, autocorrelation and power spectral density capture different statistical properties. Thermal noise is often approximated as additive white Gaussian noise over the receiver bandwidth; whiteness is a model over a frequency range, not infinite physical noise power.
Keep power ratios consistent
Signal-to-noise ratio compares signal power with noise power at a stated point in the receiver. In decibels, . For thermal noise, available noise power is approximately under the usual matched, classical-noise assumptions. Noise figure describes how much a component degrades SNR.
Try it
If signal power is 100 times noise power, SNR is 20 dB. Doubling receiver noise bandwidth doubles ideal white-noise power when temperature and spectral density stay unchanged.
Check your understanding
Distinguish random noise from deterministic interference. Explain why bandwidth and temperature belong in a noise calculation. Study correlation, Gaussian distributions and receiver-noise examples next.
Pause and recall
Without looking back, explain the main idea, recall a key definition or formula, and describe when it applies. Include assumptions and units where relevant. Revisit any step you could not explain.