Hybrid load prediction model of 5G base station based on time series decomposition and GRU network with parameter optimization
Guoxiang Hua,
Yan Sun,
Weiwei Li
Abstract:To ensure the safe and stable operation of 5G base stations, it is essential to accurately predict their power load. However, current short‐term prediction methods are rarely applied rationally in pertinent circumstances to the features of base station power load over time. For high accuracy and generalization capabilities, this work proposes a hybrid approach that combines gated recurrent unit (GRU) with particle swarm optimization (PSO) and completes ensemble empirical mode decomposition with adaptive noise … Show more
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