Teletraffic Performance of Hierarchical Cellular Network in Different Populations of Slow Mobile Generated Traffics

• Main Author: Ali, Abdul Halim
• Format: Thesis
• Language: English; English
• Published: 1999
• Online Access: http://psasir.upm.edu.my/id/eprint/10452/1/FK_1999_41_A.pdf; http://psasir.upm.edu.my/id/eprint/10452/

Ever since the first analogue mobile cellular was launched 15 years ago, the growth of and demand for the cellular communications have never reached its saturation stage. The technological change from analogue to digital and now the merging of cellular mobile and personal communications system (peS) have already taken place. All of these changes will tremendously increase in the number of mobile communication users which leads to serious Quality of Service (QoS) problems. The objective of layered network architecture comprising a hierarchical layer of different cell sizes is to provide increased capacity and alternate routes for calls that may be otherwise blocked when parts of the network are congested. Thus, this configuration results in higher traffic capacity and improves the quality of service (QoS) of the network. Today, teletraffic problems present a much greater challenge than when the first analogue mobile cellular was launched. The coming of hierarchical network makes it even more challenging to the network designers to design the hierarchical network structure that is able to cope with the huge growth of traffic and provide acceptable QoS to the customers at the same time. In this study two types of cell sizes were used whereby the upper layers are of large cell radius known as macrocells and the lower layers are of small cells radius size known as microcells. The hierarchical structure of cells serves two purposes. Firstly, the cells of small and large radius provide a more economically efficient system for higher and lower traffic densities, respectively, and secondly the subscribers of lower and higher mobility can efficiently be served in small and large cell radius, respectively. Two types of users' mobility patterns within the layers were included in the model. They were fast mobile low traffic density users travelling at the speed of 9 m/s and slow mobile high traffic density moving at the speed of 1.5 m/s. These basically represent the vehicular and pedestrian traffic respectively. Three models for two different categories of slow mobile high traffic densities known as independent model, semi-interactive and fully-interactive model were simulated. They were analysed for 50% and 70% slow mobile high traffic densities.