access icon free Synthetic method to generate α-µ distributed variants

Although the transformation method can essentially be used to generate any distribution, its application to the α-µ model involves inversion of the incomplete gamma function. Such inversion of a special function does not lead to a closed-form expression but is usually implemented using iterative methods, which heavily burden any simulation machine. By introducing a novel synthetic α-µ variant generation method, free from iterations and special functions, the proposed approach will be appropriate for building generalised real-time fading simulators.

Inspec keywords: fading channels; gamma distribution; iterative methods

Other keywords: generalised real-time fading simulators; α–μ distributed variants; novel synthetic α-μ variant generation method; special functions; iterative methods; incomplete gamma function; transformation method

Subjects: Interpolation and function approximation (numerical analysis); Radio links and equipment; Other topics in statistics

References

    1. 1)
    2. 2)
      • 12. Conover, W.J.: ‘Practical nonparametric statistics’ (John Wiley & Sons, New York, 1980, 3rd edn).
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
      • 13. Olver, F.W.J., Lozier, D.W., Clark, C.W., Boisvert, R.F.: ‘NIST handbook of mathematical functions’ (Cambridge University Press, London, 2010).
    8. 8)
    9. 9)
    10. 10)
      • 8. Proakis, J.G., Masoud, S.: ‘Digital communications’ (McGraw-Hill, New York, 2008, 5th edn).
    11. 11)
    12. 12)
    13. 13)
    14. 14)
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2014.3393
Loading

Related content

content/journals/10.1049/el.2014.3393
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading