- 2068 Bhadra (CS I) · 4+4 marks
White noise PSDF and AC; properties of autocorrelation
Short answer
White noise has flat PSD S(f) = N0/2 for all f, leading to autocorrelation function R(τ) = (N0/2)δ(τ). Key properties of autocorrelation include even symmetry, maximum at zero lag equal to average power, a Fourier pair with PSD via Wiener–Khinchin, periodicity for periodic signals, and convergence to the squared mean for large lags.
Define white noise with PSDF and auto correlation function. State the properties of auto correlation function.
White noise, its PSDF and AC function
White noise is an idealised random noise whose power spectral density is flat (constant) over all frequencies, like white light containing all colours. Thermal and shot noise are nearly white up to very high frequencies ( Hz), so the model is accurate for any practical receiver bandwidth. It is usually also assumed Gaussian, zero-mean (AWGN).
PSD (two-sided):
where (W/Hz), = Boltzmann constant and = equivalent noise temperature.
Autocorrelation (inverse Fourier transform of PSD, using ):
S_W(f) R_W(tau)
| ^ (N0/2) delta
N0/2+----------------- |
| |
----+-----------------> f ------+------> tau
0 0
Meaning: for every , so any two samples of white noise, however close, are uncorrelated (and independent if Gaussian). The total power is infinite, which is why white noise is only a model; after any filter with finite bandwidth the power becomes finite.
Properties of the autocorrelation function
- Even symmetry: .
- Value at origin = mean-square value (power): (for an energy signal, ).
- Maximum at origin: for all .
- Fourier pair with PSD (Wiener–Khinchin): and .
- Periodicity: if is periodic with period , is also periodic with .
- DC component: if has mean and no periodic part, as .
White noise satisfies these: is even, maximum at , and its Fourier transform is the flat PSD.
✓ Answer checked by Claude Opus 5.5 (high effort)
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