Additive White Guassian Noise properties (Newbie question)

Started by Deamon in comp.dsp11 years ago 9 replies

I am taking a course in Digital communication. I had a topic on the concept called Bipolar Amplitude Shift Keying in which I heard AWGN . It...

I am taking a course in Digital communication. I had a topic on the concept called Bipolar Amplitude Shift Keying in which I heard AWGN . It is said it has 3 properties Autocorrelation (dirac delta), Power spectral Density of (N/2) and PDF of Guassian Shape please can anyone explain how this properies make a AWGN unique . Any pointers to web resources will be appreciated. Thanks .


xcorr - biased and unbiased

Started by puckman in comp.dsp13 years ago 4 replies

hello, Could someone please tell me what is the difference between biased and unbiased? And when do I use biased or unbiased? or any restriction...

hello, Could someone please tell me what is the difference between biased and unbiased? And when do I use biased or unbiased? or any restriction to use one of each? I was trying to implement Linear Predictor by using autocorrelation. When I tested with sine wave, biased correlation provides a better shape, but has a scaling problem in a peak of sinewave. Unbiased has a less scaling problem,...


spectral factorization using cepstral deconvolution

Started by emre in comp.dsp15 years ago 12 replies

Hi there, I want to find the minimum phase spectral factor of a real autocorrelation sequence using cepstral deconvolution. However I run into...

Hi there, I want to find the minimum phase spectral factor of a real autocorrelation sequence using cepstral deconvolution. However I run into problems when the spectrum has a null. Is there a way to get around this problem, or is the cepstral deconvolution doomed to fail in case of a null? Could anyone suggest me another efficient method that will take about the same time for a sequence of len...


Modifying Jakes Method to simulate multipath fading channel

Started by sasuke in comp.dsp12 years ago 10 replies

Hello I have read through Jakes' paper regarding multipath simulation and I have also gone through the effort of coding it and getting the...

Hello I have read through Jakes' paper regarding multipath simulation and I have also gone through the effort of coding it and getting the waveforms like the autocorrelation function and the power spectral density. Now I want to take it one step further. I want to modify the Jakes method to simulate a multipath channel which is not completely dtereministic. Here's what I intend to do 1. Jake...


Power spectrum and autocorrelation form a fourier transform pair

Started by amlangford in comp.dsp14 years ago 6 replies

Im an undergraduate in DSP having now completed the taught modules of the course covering the usual introduction level signal processing theory...

Im an undergraduate in DSP having now completed the taught modules of the course covering the usual introduction level signal processing theory such as sampling theorm, fourier analysis, convolution, correlation. I'm now undertaking my thesis, the detection of modern comms signals, and have been reading up on the associated wealth of theory and papers, in particular statistical signal processing. ...


Network analysis using chirp signal.

Started by Dimitar Penev in comp.dsp17 years ago 3 replies

Hello All, I am creating the simple network analyzer using the general purpose DAQ board. Currently I am testing the system using linear...

Hello All, I am creating the simple network analyzer using the general purpose DAQ board. Currently I am testing the system using linear chirp (tone with sweeping frequency) exitation signal x. Then I correlate the output of the system y with x and got estimation of the impulse system response h. FFT it to get frequeny response H The procedure works because the autocorrelation of...


Complex Psudo-Noise Sequences

Started by porterboy in comp.dsp17 years ago 4 replies

I am trying to design a training sequence for a communications system. I originally had a real signal and I was using a periodic M-Sequence as...

I am trying to design a training sequence for a communications system. I originally had a real signal and I was using a periodic M-Sequence as the training signal (FYI an m-sequence is a special series of {+1,-1} which has an autocorrelation function which is almost a perfect spike: very like white noise). However, since I am doing bandpass communication, a real signal is double sideband, ...


how to find the autocorrelation and spectrum of the receiver signal in mobile communication?

Started by kiki in comp.dsp17 years ago 2 replies

Hi all, I am wondering about the simplest model in mobile communicaiton, multipath. Suppose the received signal has random uniform [0, 2*pi]...

Hi all, I am wondering about the simplest model in mobile communicaiton, multipath. Suppose the received signal has random uniform [0, 2*pi] phase due to multipath fading, and also has Rayleigh distribution on its amplitude(assuming no direct line path), and also has doppler frequency shift in carrier frequency. The signal then can be modelled as r(t)=A*exp(j*2*pi*(f+delta_f)*t +...


Autocorrelation of Zadoff_chu sequence

Started by mathu_09 in comp.dsp12 years ago

Hi I have a query with the Zadoff_chu sequence I have the following matlab code I generated the zad_off chu sequence then made a circular...

Hi I have a query with the Zadoff_chu sequence I have the following matlab code I generated the zad_off chu sequence then made a circular shift with factor of 6. tried to correlate the shifted version with the original as expected the peak has shifted but iam unable to get the location of the peak mathematically and what i dont understand is why is the peak shifting based on the factor...


Discrete-Time Stochastic Signal Definitions in Proakis

Started by Randy Yates in comp.dsp16 years ago 4 replies

Hi Folks, We're using Proakis' "Digital Communications" (4th ed.) for our (guess what?) digital communications course at NCSU. In the second...

Hi Folks, We're using Proakis' "Digital Communications" (4th ed.) for our (guess what?) digital communications course at NCSU. In the second chapter, which is a review of probability and stochastic processes, Proakis defines the discrete-time autocorrelation function as Rxx(n,k) = (1/2) * E[X(n) * X(k)'], where "'" denotes complex conjugate. My question: Where does the "1/2" come ...


ZADOFF-CHU SEQUENCES (in LTE)

Started by Manolete in comp.dsp12 years ago 2 replies

Hello, I'm studying Zadoff-Chu sequences properties. If you take a look into "http://en.wikipedia.org/wiki/Zadoff%E2%80%93Chu_sequence" you...

Hello, I'm studying Zadoff-Chu sequences properties. If you take a look into "http://en.wikipedia.org/wiki/Zadoff%E2%80%93Chu_sequence" you can see the generation of the sequence. Well, in LTE (in P-SS) we use 3 sequences of length 63 (N=63) and roots u=25,29,34. All books say that these sequences have an ideal periodic autocorrelation function and a constant periodic cross-correlation equal...


Any statistical information in the phase of a signal?

Started by westocl in comp.dsp10 years ago 7 replies

In basic random signal modeling, in general we toss away any information that could be assertained from the phase of a signal. Maybe we...

In basic random signal modeling, in general we toss away any information that could be assertained from the phase of a signal. Maybe we compute the autocorrelation and work with the PSD of a signal. The phase is forever lost and assumed to be random... but we assume the amplitude squared (hence the amplitude) of the F.T. on average can tell us something. (assuming stationarity). Ok, heres a...


help: how to determine wide-sense stationarity from a graph?

Started by Anonymous in comp.dsp15 years ago 1 reply

Hi, everyone please tell me how to determine that a random process is wide-sense stationarity from it's autocorrelation graph or power...

Hi, everyone please tell me how to determine that a random process is wide-sense stationarity from it's autocorrelation graph or power spectrum graph. Thanks net


pink noise

Started by sham...@gmail.com in comp.dsp14 years ago

How can identify pink noise statistically, as we identify that this signal is speech and this is noise, because using autocorrelation and...

How can identify pink noise statistically, as we identify that this signal is speech and this is noise, because using autocorrelation and harmonics analysis leads to pink noise identified as signal.


Correlation Function/Decorrelation Time Estimate Discrepancies

Started by Greg Heath in comp.dsp17 years ago 2 replies

When I was analyzing some time-series data, I obtained the autocorrelation function and corresponding estimate of the 1/e (=0.3679) decorrelation...

When I was analyzing some time-series data, I obtained the autocorrelation function and corresponding estimate of the 1/e (=0.3679) decorrelation time by ifft-ing the power spectral density. As a check, I used the MATLAB function xcorr. As can be seen below and in the plot for the test function z = (x-mean(x))/std(x), x = t.*exp(-t), The functions and decorrelation time estimates were signif...


does WGN(white Gaussian noise) imple zero mean?

Started by kiki in comp.dsp17 years ago 18 replies

Hi all, I read through several books but did not get clarification on whether WGN(white Gaussian noise process) imply zero mean or...

Hi all, I read through several books but did not get clarification on whether WGN(white Gaussian noise process) imply zero mean or not... Another confusion I have is that the definition of WGN is it has flat power spectrum density, let's say S(f)=1, then Rx(t)=delta(t) is its autocorrelation function, I don't see how people say the power of this noise process is E((x(t))^2)=sigma_x, ...


Cyclic Spectral Estimation (Matlab)

Started by ryujin_ssdt in comp.dsp14 years ago 3 replies

Cyclostationarity is a common property of man-made digital signals that has a vast number of uses in digital...

Cyclostationarity is a common property of man-made digital signals that has a vast number of uses in digital communications: http://spincom.ece.umn.edu/papers04/bib05eurasip.pdf To make use of cyclostationarity it is necessary to estimate the Cyclic Cross Autocorrelation or the Cyclic Cross Spectrum of the received signals. In a simulation how do I estimate these two values?? I have ...


cyclostationary signal

Started by part...@yahoo.com in comp.dsp14 years ago

Hello all, I am trying to implement the algorithm found in the paper "Carrier Frequency and Chip Rate Estimation Based on Cyclic Spectral...

Hello all, I am trying to implement the algorithm found in the paper "Carrier Frequency and Chip Rate Estimation Based on Cyclic Spectral Density of MPSK Signals" by Z. Zhang et. al. IEEE Basically, the algorithm states that if I calculate the cyclic autocorrelation of the signal and take its fourier transform and plot in in 3D (x-axis is chip rate, y-axis is the frequency, z-asix is the...


tone burst time measurements?

Started by Ronald H. Nicholson Jr. in comp.dsp16 years ago 1 reply

There's been a fair amount of discussion in this newsgroup about the various ways to measure the frequency of a tone burst (time between...

There's been a fair amount of discussion in this newsgroup about the various ways to measure the frequency of a tone burst (time between zero crossings, interpolated fft, padded fft, phase vocoder, autocorrelation, etc.), given the assumption of its presence somewhere in time. How about the flip side of the time-frequency trade-off, the various algorithms to measure the location of a tone b...


urgent

Started by dew in comp.dsp15 years ago 1 reply

hi can someone please explain the meaning of this code its about computing the autocorrelation function IN MATLAB r1=[zeros(1,101)]; for...

hi can someone please explain the meaning of this code its about computing the autocorrelation function IN MATLAB r1=[zeros(1,101)]; for i=1:1:50 x=rand(1,5000); r=zeros(1,101); fori=1:1:50 z=[x zeros(1,i)]; y=[zeros(1,i) x]; r(51+i)=sum(z.*y)./(5000-i); end r(51)=sum(x.*x)./(5000); z=[ zeros(1,i) x]; y=[x zeros(1,i)]; r(i)=sum(z.*y)./(5000-i);