In the post on Rayleigh channel model, we stated that a circularly symmetric random variable is of the form , where real and imaginary parts are zero mean independent and identically distributed (iid) Gaussian random variables. The magnitude which has the probability density,
is called a Rayleigh random variable. Further, the phase is uniformly distributed from . In this post we will try to derive the expression for probability density function (PDF) for and .
The text provided in Section 5.4.5 of [ELECTRONIC-COMMUNICATION:PRADIP] is used as reference.
The probability density function of is
Similarly probability density function of is
As and are independent random variables, the joint probability is the product of the individual probability, i.e,
The joint probability that the random variable lies between and and the random variable lies between and is,
Conversion to polar co-ordinate
Figure: Cartesian co-ordinate to polar co-ordinate
The area is Cartesian co-ordinate form is equal to the area in the polar co-ordinate form.
Summarizing the joint probability density function,
Since and are independent, the individual probability density functions are,
Simple Matlab/Octave simulation model is provided for plotting the probability density of and . The script performs the following:
(a) Generate two independent zero mean, unit variance Gaussian random variables
(b) Using the hist() function compute the simulated probability density for both and
(c) Using the knowledge of the equation (which we just derived), compute the theoretical probability
density function (PDF)
(d) Plot the simulated and theoretical probability density functions (PDF) and show that they are in good agreement.
Figure: Simulated/theoretical PDF of Rayleigh random variable
Figure: Simulated/theoretical PDF of uniformly distributed theta random variable
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