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The Rake receiver is simply a filter matched to the channel impulse response and as such it does not require spreading. But a matched filter does not work very well, so without spreading gain the performance may not be good enough.
You should read up on the relation between the spectrum and autocorrelation function. The power spectral density (PSD) is simply the fourier transform of the autocorrelation function. A narrow bandwidth therefore implies a "broad" autocorrelation function.
The conclusion is correct, but saying...
Re: equlisers...
There is no fundamental difference.
I suppose the term equalizer traditionally means "making frequencies equal." In order to estimate a distorted signal, that is exactly what you have to do. On the other hand, the term is now also being used in the context of non-stationary...
I do not follow your line of reasoning. What I think you may be doing is this.
The desired signal is band limited and deterministic. You have a noise signal with greater bandwidth than the desired signal. If you sample at the rate corresponding to the desired signal, there will be aliasing for...
The quantization noise amplitude response for the 1st order sigma-delta modulator is sin^2(pi f/fs), which is rather flat at +/- fs/2. Is that what you mean? The amplitude response can be computed rather easily from the difference equations (cf., for example, this toy paper [1]).
[1] **broken...
Oversampling means that you sample at a higher rate than the signal rate. Since the signal changes slowly wrt. the sampling rate, neighboring samples are correlated.
But if you normalize the correlation delay to the sampling rate, then oversampling just gives you a greater resolution of the...
You are comparing different things. Mutual information determines the capacity of a channel, whereas outage probability is the probability that the capacity is below a certain threshold.
Given a constant filter order, the greater the cutoff frequency the better the DC offset rejection, but signal distortion also increases with increasing cutoff frequency. The optimal setting depends on the amount of DC offset generated in the ADC and how much you care about error due to distortion.
Re: How to design the matlab code for LMS adaptive equilizat
This is pretty much it:
w = 1
mu = .01
foreach x
y = H x + n
x_est = w' y
e = x - x_est
w = w + mu x e'
end
where x is the transmit symbol, H is channel, n is additive noise, y is the received signal, w is the equalizer...
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