| Description |
the function simulates a circuit-switched system, with a finite number of channels, and with calls coming and staying according to values from a given probability distribution.
The idea is to determine probability of losing calls, given arrival rates, holding times and available channels.
%%function results=simulate_trunked_v2(C,N,InterArrivalTimeDist,par1_IAT,par2_IAT,HoldingTimeDist,par1_HT,par2_HT)
%
%Simulation of call traffic in a trunked communication network
%Mobile Communication Technology ( Mr. Rajesh Sharma )
%Original by: Saurav Ratna Tuladhar <sauravtuladhar@gmail.com>, IOE/TU
%Modified by: L. Emiliani
%-----------------------------------------------------------------------
%
%Example
%the following is an example of usage. 1000 events, 10 channels, 49000
%seconds mean IAT, 100 as shape parameter.., weibul IAT, normal HT, 8 hours
%mean holding time, and a variance of 20 seconds...
%
%simulate_trunked_v2(1000,10,'wei',49000,100,'nor',8*3600,20)
%
%Modifications: increased flexibility in the probability distributions
%employed, increased flexibility in system parameters (sim. duration and
%channels), turned mfile into function
%
%INPUTS
%C: number of call events
%N: number of trunked channels
%InterArrivalTimeDist: One of 'exp','wei','poi' for exponential, weibull or
%poisson distribute interarrival times.
%
%The exponential distribution:
%http://www.itl.nist.gov/div898/handbook/eda/section3/eda3667.htm
%
%The poisson distribution:
%http://www.itl.nist.gov/div898/handbook/eda/section3/eda366j.htm
%note that i mix discrete and continuous distributions here...i know is not
%theoretically sound.
%
%The Weibull distribution:
%http://www.itl.nist.gov/div898/handbook/apr/section1/apr162.htm#Formula's%20and
%note that alfa=Par1 and gamma=par2 and that they do not correspond to mean
%and variance. there is a transformation involving the gamma function. mean
%is close to PAR1, while variance might not!!! the function returns and
%displays the mean and variance that correspond to par1 and par2
%
%par1_IAT,par2_IAT: parameters 1 and 2 of the selected IAT distribution. in
%minutes. For 'exp' or 'poi', leave par2 as EMPTY ([])
%
%HoldingTimeDist,par1_HT,par2_HT: one of 'exp','nor','wei', for
%exponential, normal or weibull holding times. par1 and par2 are the
%parameters of the distributions. for 'exp', leave par2 as EMPTY ( [] ) |
