Analysis and Modeling of Intelligent Channel Allocation Techniques in Mobile Communication Systems
Year: 2025
Type: article
Abstract: This study is on the analysis and modeling of intelligent channel allocation techniques in mobile communication systems where different channel allocation techniques were considered in mobile communication systems. Also, the different channels which are used in the cellular networks were sufficiently described. Various parameters in mobile communication system that are related to channel allocation techniques and blocked calls were identified and discussed. Data collection was carried out from the Network Switching Center of a highly established and reputable Telecommunication Operator. Data were collected both from the Base Transceiver Stations (BTS), the Base Station Controller (BSC) and the Mobile Switching Centre (MSC), at different locations in Nigeria. These data were collected at different times on monthly basis for a period of thirty six (36) months in the course of this study. Proteus software was used to analyze data collected to enhance the simulation set up. A model (GRACE MODEL) of intelligent channel allocation technique algorithm was developed to reduce the call blocking and also call dropping probability. To authenticate the effectiveness of the proposed algorithm, the simulation result was demonstrated respectively showing normal capacity; over capacity; rerouting to neighbouring sector, e.t.c. It was observed that with the use of the proposed channel re-assignment strategies algorithm, the radio coverage at large distances had more increase in the system channel capacity. It was also observed that the blocked calls (the chance that a call will have no service) were highly reduced due to intelligent philosophy in the developed model. Additionally, the model helped to scale up performance and provided great improvement in network spectral and energy efficiency.
Authors: Ufuah Charles, Usiade Rex
Institution: Delta State Polytechnic Otefe-Oghara
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6930738952
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