Performance of Wireless Networks Using Migration Processes for Mobility Modeling -Edición Única

Abstract

The principal idea of a communication system is to provide service to the users at any time, and this service needs to be fast, efficient and of good quality. The increasing demand of mobile cellular telecommunication systems has raised the necessity to employ efficiently the limited resources to maintain a good grade of service. In order to determine the optimal use of the resources, the dynamic population analysis is important due to the impact of mobility over performance measures such as blocking probability, multi-user interference, location area design and handoff process. Knowing the characteristics of customers' mobility, we can predict the customers' density on an attractor, on a cell, on a system; and as a result, the system could adjust by itself the assignment of channels according to the conditions of the traffic demand, and maintain the same system performance. This work considers the use of the reversibility migration processes, [1], in modeling the customer's mobility in a spatial area and time of day. In summary, we use the concept of Social Grouping Behavior considering the principal activity centers denominated attractors. Customers' distribution based on attractors is employed to calculate the blocking probability variations during the day, and predict the position and mobility of them. The objective of this work is to present a mobility model, based on migration processes, which can help measure performance of a wireless cellular network to get a better use of the resources.