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How does oversampling affect white Gaussian noise correlation?
If we receive a signal assuming white Gaussian noise channel and we want to over-sample the signal to ensure high correlation between signal samples, does the oversampling affect the noise correlation (which is suppose to be uncorrelated). Join ResearchGate to ask questions, get input, and advance your work.
How to add white Gaussian noise to AWGN?
To have the function measure the power of in before adding noise, specify signalpower as ‘measured’. out = awgn (in,snr,signalpower,randobject) accepts input combinations from prior syntaxes and a random number stream object to generate normal random noise samples. For information about producing repeatable noise samples, see Tips.
How to add Gaussian noise to a vector?
out = awgn(in,snr) adds white Gaussian noise to the vector signal in. This syntax assumes that the power of in is 0 dBW. out = awgn(in,snr,signalpower) accepts an input signal power value in dBW. To have the function measure the power of in before adding noise, specify signalpower as ‘measured’.
How to add white Gaussian noise in MATLAB?
View MATLAB Command. Generate white Gaussian noise addition results using a RandStream object and the reset object function. Specify the power of X to be 0 dBW, add noise to produce an SNR of 10 dB, and utilize a local random stream. S = RandStream ( ‘mt19937ar’, ‘Seed’ ,5489); sigin = sqrt (2)*sin (0:pi/8:6*pi); sigout1 = awgn (sigin,10,0,S);
When is sampling frequency twice the system bandwidth?
When sampling frequency is the twice the system (hardware) bandwidth, the sampled noise is almost white noise. In most cases, the hardware bandwidth equals the bandwidth of the signals from a channel. Correlation-based detectors sometimes require oversampling to guarantee a correlated primary signal.
How is the RMS of white noise calculated?
Namely if you use the same LPF yet with two different samplings rates the RMS of the noise is the same. Now, the theoretical RMS of White Noise is given by its PSD which is a constant. The RMS of the sampled noise is the constant value multiplied by the BW of the LPF in the sampling chain.
How often should oversampling be used for correlation?
In general it is good practise to use oversampling more than two times of your signal frequency even with correlation techniques.