An additive Gaussian white noise process in time is an additive Gaussian white noise process in frequency, with the same distribution in both domains. (So therefore as far as a mathematical function it is just a change of variable from time to frequency when using a unitary Fourier transform). Let's also remind ourselves of what AWGN is White noise = noise with a constant power spectral density. The term comes from light, if you have all wavelengths of light present, the resulting light is white. Gaussian noise = noise that follows a normal distribution Yes, many DSP texts (as well as Wikipedia's definition of a discrete-time white noise process) and many people with much higher reputation than me on dsp.SE say that uncorrelatedness suffices for defining a white noise process, and in the case of white Gaussian noise it does because Gaussianity brings in the jointly Gaussian property: a
Lecture 4: Gaussian white noise and Wiener process Dr. Roman V Belavkin MSO4112 Contents 1 Gaussian process 1 2 White noise 1 3 Linear transformation of white noise 2 4 Wiener process 3 References 3 • If x(t) is white noise, then E{y(t)} = e−αty(0) and k y(t 1,t 2) = g 2 Z t 1 0 Z t 2 0 e−α(t
Expert Answer. Matlab Code for BER of BPSK in AWGN Channel : N = 10^6 % number of bits or symbols rand ('state',100); % initializing the rand () function randn ('state',200); % initializing the randn () …. 1 Matlab Simulation of BPSK modulation under an Additive White Gaussian Noise (AWGN) Channel Write a Matlab script that simulates BPSK

$\begingroup$ So the discrete Gaussian white noise has no continuous time equivalent? $\endgroup$ - user1237300. Mar 26, 2020 at 19:40 $\begingroup$ @user1237300 I'm not sure what did mean by equivalent, but continuous Gaussian white noise exist! $\endgroup$ - Mohammad M.

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    • white noise vs gaussian noise