The Journal of China Universities of Posts and Telecommunications ›› 2024, Vol. 31 ›› Issue (5): 42-48.doi: 10.19682/j.cnki.1005-8885.2024.0014

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Parameter estimation of Nakagami-Gamma shadow fading model based on minimum KL divergence

  

  • Received:2023-03-01 Revised:2024-01-02 Online:2024-10-31 Published:2024-10-31

Abstract: The Nakagami-Gamma ( NG) shadow fading model based on the moment-based method ( MoM) generates lower tail approximation, which is inaccuracy when the gamma random variables are replaced by the lognormal random variables. The channel parameters of composite NG shadow fading based on the method of minimizing the Kullback- Leibler ( KL) divergence were estimated and a closed-form expression for the system bit error rate ( BER) was derived in this paper. The simulation results show that the KL estimated parameters solve the lower tail approximation problem, and the replacement effect of the lognormal function by the gamma function is better than the MoM when the shading parameters are around the typical value of 4 dB - 9 dB. Moreover, the KL method has a lower mean square error ( MSE) value for the channel analysis.

Key words:

moment-based method ( MoM), shadow fading channel, Nakagami-Gamma ( NG), Kullback-Leibler ( KL)