Estimating Base Station Traffic and Throughput Using Machine
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.
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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.
Accurate traffic forecasting in base station networks is crucial for efficient network management, resource allocation, and ensuring quality of service. This paper introduces BetaStack,
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 stations.
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 attention
This research focuses on analyzing and predicting traffic and throughput at base stations in cellular networks using machine learning algorithms. The main research area is network
The data used in this paper comes from the hourly traffic data of the base station cell from March 1 to April 19, 2018 provided by MathorCup university mathematical modeling challenge.
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 traffic has high
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 traffic with
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.
The hourly data collected from 22 base stations in Daxing District, Beijing, spanning from 0:00 on August 5, 2021, to 23:00 on September 5, 2021, underwent statistical analysis.
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