bstract bstract bstractComputer simulation modelling has the advantage of flexibility and modelling accuracy. However, it has Computer simulation modelling has the advantage of flexibility and modelling accuracy. However, it has Computer simulation modelling has the advantage of flexibility and modelling accuracy. However, it has Computer simulation modelling has the advantage of flexibility and modelling accuracy. However, it has limitations in its ability to be used to simulate cell loss rate when deriving t limitations in its ability to be used to simulate cell loss rate when deriving t limitations in its ability to be used to simulate cell loss rate when deriving t limitations in its ability to be used to simulate cell loss rate when deriving t required for data services to guarantee specific Quality of Service (QoS) requirement. Cell loss rates are required for data services to guarantee specific Quality of Service (QoS) requirement. Cell loss rates are required for data services to guarantee specific Quality of Service (QoS) requirement. Cell loss rates are required for data services to guarantee specific Quality of Service (QoS) requirement. Cell loss rates are simulated with excessive and unacceptable computer simulation run times. This limitation was overcome simulated with excessive and unacceptable computer simulation run times. This limitation was overcome simulated with excessive and unacceptable computer simulation run times. This limitation was overcome simulated with excessive and unacceptable computer simulation run times. This limitation was overcome in an earlier publication in an earlier publication in an earlier publication in an earlier publication by the author using an integrated simulation technique. This paper, therefore, by the author using an integrated simulation technique. This paper, therefore, by the author using an integrated simulation technique. This paper, therefore, by the author using an integrated simulation technique. This paper, therefore, describes the application of the integrated simulation technique for deriving the optimum resources describes the application of the integrated simulation technique for deriving the optimum resources describes the application of the integrated simulation technique for deriving the optimum resources describes the application of the integrated simulation technique for deriving the optimum resources required for data services in an asynchronous transfer mode (ATM) based priva required for data services in an asynchronous transfer mode (ATM) based priva required for data services in an asynchronous transfer mode (ATM) based priva required for data services in an asynchronous transfer mode (ATM) based priva (WAN) to guarantee specific QoS requirement. The simulation tool drastically cuts the simulation run (WAN) to guarantee specific QoS requirement. The simulation tool drastically cuts the simulation run (WAN) to guarantee specific QoS requirement. The simulation tool drastically cuts the simulation run (WAN) to guarantee specific ...
The increase in GSM mobile station (MS) density, without a corresponding increase in radio channel resource capacity, reduces the quality of service (QoS) standard provided to users. Attempts to improve the QoS standard usually leads to the creation of new base stations (BS) with the consequent reduction in the existing cell sizes. Although, the available network capacity is increased, this happens at the expense of increased numbers of call handoversSuch increase is usually accommodated by resource reservation. How well the reservation is made greatly influences the GSM network quality of service (QoS) and the general BS resource utilization. This work presents a radio channel resource reservation technique for GSM handover calls. A typical GSM network architecture was modeled using an integrated modeling technique in a MATLAB block oriented simulation environment. The analytical part of the model was developed using the Markov chain principle and validated using the existing popular Lee's queuing model. The relationships between the handover call blocking probability, fresh call blocking probability, the number of resources to be reserved and traffic intensity were established. Simulation results were analyzed and a method of determining the optimum number of resources that can be reserved for handover calls for a given BS resource capacity was presented.
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