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The impacts of customer behaviors on the blocking probabilities and the performance measures in wireless networks were studied. Customer behavior information was acquired from a data warehouse and served as input vectors for an analytical model to calculate desired unknowns (information). In order to assure the information the authors provided for their network operators was accurate and reliable, the Monte Carlo simulator was implemented to mimic real world situations. In analytical modeling, the distribution function in the inter-arrival time was assumed to be exponential decay without any proof.
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