Optimizing Call Setup Success (CSSR) Parameters In Mobile Communications Using K-Nearest Neighbor (K-NN) - Bramantyo, Hutama Arif; Mujahidin, Irfan (JAICT, 2023)
The evaluation of the mobile communication network inside the cellular communication system, often known as the Global System for Mobile Communication, is crucial to achieve optimal call quality. The Call Setup Success Rate (CSSR) is a measure that plays a significant role in determining the performance of the mobile network, alongside various other factors. The mobile network's performance may decrease if the Call Setup Success Rate (CSSR) number is below the expected standard. The CSSR outcome is influenced by multiple variables that lack a specific formula or exhibit no discernible relationship with one another. The individual responsible for optimizing decisions in the real case is an operator or an engineer who relies on their experience to inform their choices. Nevertheless, even those with previous expertise in this domain may encounter difficulties determining the most effective approach for optimizing CSSR parameters since they must consider the interconnections among the many inherent values in these parameters. In order to achieve this objective, it is necessary to employ pattern recognition algorithms, among which the k-nearest Neighbor (k-NN) technique is included. In this study, the k-nearest Neighbor method will be employed to assist novice engineers in determining the optimization method for enhancing CSSR performance. Certain data from the OMC-R are utilized for the purpose of enhancing the performance of the CSSR and determining the feasibility of employing the k-NN pattern recognition approach to improve the CSSR. The efficacy of the k-Nearest Neighbors (k-NN) algorithm in providing an optimal solution, as determined by the operator or engineer on behalf of the telecommunication service provider, serves as a key indicator of the system's overall success. The implementation of CSSR optimization utilizing the k-NN algorithm decision has achieved a successful outcome, with 89.65% of the total data being accurately processed.