Download PDFOpen PDF in browserLSTM Neural Network Architecture and Hyperparameter Exploration for Handover Simulation in 5G NetworkEasyChair Preprint 116534 pages•Date: January 2, 2024AbstractThis paper presents a machine learning model for optimizing a handover process in 5G networks. The data for learning and testing is simulated using NS3. By using RNN with LSTM layer, model is enable to decide which cell to handover to provide the highest download success rate. Key of this analysis is exploring the hyperparameter of the model such as hidden nodes, epoch, dropout rate to provide the highest download success rate. Keyphrases: Dropout, Epoch, Handover, LSTM, RNN, hidden nodes
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