Implementation of Self-Organizing Network (SON) on Cellular Technology base on Big Data Analytic
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The development of cellular technology will be directly proportional to the increasing requirement in various aspects, such as the speed of data transmission (velocity), data variations (variety), and data storage media (volume). The increase in various aspects will have a direct impact on the growth of internet users worldwide. In relation to that, the demand for increased capacity and coverage becomes a necessity because users access the networks using the same resources by utilizing resource sharing mechanism. Self Organizing Network (SON) is one of the solutions to make the system more efficient with guaranteed Quality of Experiment (QoE). SON can create an automated network with a self-optimization, self-configuration and self-healing mechanism. Big Data is leveraged in the network analytics as a reference for decision-making activities in the network automation process. In this paper, SON using Big Data analytics on 5G network is compared with SON on 4G network as the previous network technology. It is suggested that on 5G networks, Big Data changes the SON detection paradigm from reactive to proactive. Detecting problems starts with data collection and analysis of possible network problems. By predicting network problems early, solving network problems can be done faster. Additionally, by using Multi-hop relay, the distance between User Equipment (EU) and Base Station (BS) will be shorter. Therefore, the aim of increasing capacity and coverage can be fulfilled.
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