Deriving cdf of ricean distribution + help

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SUMMARY

The discussion focuses on deriving the cumulative distribution function (CDF) of the Rice distribution using the generalized Marcum Q function. The key formulas presented include the Marcum Q function, the probability density function (PDF) of the Rice distribution, and the relationship between the CDF and the PDF. The user attempts to express the CDF as F_{r}(r) = 1 - Q_{M}(A/\sigma, r_{min}/\sigma) and seeks validation of their approach, which involves substituting variables and integrating the PDF. The user confirms that the CDF is indeed the integral of the PDF, indicating a solid understanding of the mathematical principles involved.

PREREQUISITES
  • Understanding of the Rice distribution and its properties
  • Familiarity with the Marcum Q function and its generalized form
  • Knowledge of modified Bessel functions, specifically I_{0}(x)
  • Basic calculus, particularly integration techniques
NEXT STEPS
  • Research the properties and applications of the Rice distribution in signal processing
  • Study the derivation and applications of the Marcum Q function
  • Explore numerical methods for evaluating integrals involving Bessel functions
  • Learn about statistical software tools for computing CDFs and PDFs, such as MATLAB or Python's SciPy library
USEFUL FOR

Mathematicians, statisticians, and engineers working in fields such as telecommunications, signal processing, and statistical modeling who require a deeper understanding of the Rice distribution and its applications.

JamesGoh
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Im aware that the generalised form of the Marcum Q function, which is

Q_{M}(\alpha,\beta)=1/(\alpha)^{M-1}\int_{\beta}x^{M}.exp(-x^{2} +\alpha^{2})/2.I_{M-1}(\alphax)dx

and the pdf of the amplitude in rice distribution is

f_{r}(r)=r/\sigma^{2}exp( (-r^{2}-A^{2})/2\sigma^{2} )I_{0}(rA/\sigma^{2})

where I_{0}(x) is a modified bessel function of first kind, zero order

and the cdf of the rice distribution is

F_{r}(r) =1-Q_{M}(A/\sigma,r_{min}/\sigma)

Using the formula for Qm and the rice pdf, I have tried to get the rice cdf, however I have not had much success. I have tried the following

Let x=r/\sigma, \alpha=A/\sigma and \beta=0

Q_{1}(\alpha,\beta)=\int_{0}^{r_{min}}=(r/\sigma)exp( (-r^{2}-A^{2})/2\sigma^{2} )I_{0}(r/\sigmaA/\sigma)d(r/\sigma)

Im aware that the cdf is the integral of the pdf and \sigma is a constant (which means it cannot change), so is my approach correct ?
 
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Im aware that the generalised form of the Marcum Q function, which is

Q_{M}(\alpha,\beta)=1/(\alpha)^{M-1}\int_{\beta}x^{M}.exp(-x^{2} +\alpha^{2})/2.I_{M-1}(\alphax)dx

and the pdf of the amplitude in rice distribution is

f_{r}(r)=r/\sigma^{2}exp( (-r^{2}-A^{2})/2\sigma^{2} )I_{0}(rA/\sigma^{2})

where I_{0}(x) is a modified bessel function of first kind, zero order

and the cdf of the rice distribution is

F_{r}(r) =1-Q_{M}(A/\sigma,r_{min}/\sigma)

Using the formula for Qm and the rice pdf, I have tried to get the rice cdf, however I have not had much success. I have tried the following

Let x=r/\sigma, \alpha=A/\sigma and \beta=0

Q_{1}(\alpha,\beta)=\int_{0}^{r_{min}}=(r/\sigma)exp( (-r^{2}-A^{2})/2\sigma^{2} )I_{0}(r/\sigmaA/\sigma)d(r/\sigma)

Im aware that the cdf is the integral of the pdf and \sigma is a constant (which means it cannot change), so is my approach correct ?
 

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