Base station traffic data analysis

Cell base station traffic prediction based on GRU

Abstract: With the expansion of Internet technology and network scale, the data volume of base station traffic also shows explosive growth. Predicting base station network

CNN-LSTM Base Station Traffic Prediction Based On Dual

The proposed CNN-LSTM model leverages a dual channel attention mechanism to bolster key feature information for long-term traffic data predictions. Specifically, a temporal

(PDF) Estimating Base Station Traffic and Throughput Using

This study explores the use of machine learning algorithms to predict traffic and downlink throughput at base stations based on hourly Key Performance Indicator (KPI) data.

Long term 5G base station traffic prediction method based on

In this research experiment, we collected historical traffic data from 67 5 G base stations in a certain region to train and evaluate a traffic prediction model for multiple base

Traffic Prediction of Mobile Communication Base Station

The mobile base station traffic data used in this paper comes from China Mobile communication operators. It collects traffic data in a base station from March 1 to April 19 in

Base Station Traffic Prediction Using Wavelet Transform and Bi

Therefore, to improve the learning efficiency and prediction accuracy, this paper presents a new method that first uses decomposition and reconstruction of wavelet transform to preprocess

Betastack: Enhancing base station traffic prediction with network

Accurate traffic forecasting in base station networks is crucial for efficient network management, resource allocation, and ensuring quality of service. This paper introduces

Mobile Base Station Traffic Prediction Based on Traffic Data

The trend is to achieve flexible allocation of communication base station resources and to achieve appropriate service, so it is important to analyse and forecast communication base station

Deep learning-based prediction of base station traffic

In order to meet this challenge, it is necessary to accurately perceive the application-level network traffic at multiple levels, such as edge network, MAN and backbone network.