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On the Ratio of Rice Random Variables

Nayereh Bageri Khoolenjani, Kavous Khorshidian

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Abstract

The ratio of independent random variables arises in many applied problems. In this article, the distribution of the ratio X/Y is studied, when X and Y are independent Rice random variables. Ratios of such random variable have extensive applications in the analysis of noises of communication systems. The exact forms of probability density function (PDF), cumulative distribution function (CDF) and the existing moments have been derived in terms of several special functions. The delta method is used to approximate moments. As a special case, we have obtained the PDF and CDF of the ratio of independent Rayleigh random variables.

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What this paper is about

The ratio of independent random variables arises in many applied problems. In this article, the distribution of the ratio X/Y is studied, when X and Y are independent Rice random variables. Ratios of such random variable have extensive applications in the analysis of noises of communication systems. The exact forms of probability density function (PDF), cumulative distribution function (CDF) and the existing moments have been derived in terms of several special functions. The delta method is used to approximate moments. As a special case, we have obtained the PDF and CDF of the ratio of independent Rayleigh random variables.

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Available abstract

The ratio of independent random variables arises in many applied problems. In this article, the distribution of the ratio X/Y is studied, when X and Y are independent Rice random variables. Ratios of such random variable have extensive applications in the analysis of noises of communication systems. The exact forms of probability density function (PDF), cumulative distribution function (CDF) and the existing moments have been derived in terms of several special functions. The delta method is used to approximate moments. As a special case, we have obtained the PDF and CDF of the ratio of independent Rayleigh random variables.

Key concepts: Random variable, Mathematics, Cumulative distribution function, Moment-generating function, Probability density function, Sum of normally distributed random variables, Ratio distribution, Statistics

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