Efficient Computation of Probability Density Function in Interfering 𝜅-𝜇 Communication Channels and Application to Fitting Measurement Data

In this paper, we propose an efficient algorithm for computing the probability density function
(PDF) of signal-to-interference ratio over 𝜅–𝜇 fading environment in wireless communications. At first, we
examine the convergence of the sum involved in the PDF expression. After that, we introduce the reminder
estimate in truncated summation by updating it with each additional term until the requested accuracy is
met. Then, we present the pseudocode of the PDF summation algorithm. In order to hint the importance
of this algorithm, we show its comparison with integration PDF approach, in terms of execution time and
precision performance. Also, due to the wide applicability of 𝜅–𝜇 fading model, we show one example of
using the proposed algorithm in overlapping measured data from indoor communication scenario with
numerical curve fit.