Base station traffic data
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Estimating Base Station Traffic and Throughput Using
Aug 21, 2024 · 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
BuptMecMigration/Edge-Computing-Dataset
5 days ago · About Edge Computing Dataset This dataset is from ISP in china and is publicly released for researches in Edge Computing. The dataset not only contains base station
Mobile Base Station Traffic Prediction Based on Traffic
May 11, 2022 · The base station traffic has non-stationary chaotic characteristics. In addition to the traditional time series prediction method ARIMA model, scholars at home and abroad also
Betastack: Enhancing base station traffic prediction with
Oct 1, 2025 · Extensive experiments on real-world data from base station cells in Guangdong, China demonstrate that BetaStack achieves significant performance improvements over both
CNN-LSTM Base Station Traffic Prediction Based On Dual
Jan 31, 2024 · Abstract Energy consumption in 5G base stations remains consistently high, even during periods of low traffic loads, thereby resulting in unnecessary inefficiencies. To address
telecom_dataset
Oct 13, 2025 · telecom_dataset About Telecom Dataset The dataset, provided by Shanghai Telecom, contains more than 7.2 million records of accessing the Interent through 3,233 base
Long term 5G base station traffic prediction method based
Dec 1, 2024 · Current methods often fall short in effectively harnessing long-term trends and spatial interconnections among base stations. To bridge these gaps, this paper introduces the
(PDF) Estimating Base Station Traffic and
Jan 1, 2024 · Abstract and Figures This study explores the use of machine learning algorithms to predict traffic and downlink throughput at base
BuptMecMigration/Edge-Computing-Dataset
OverviewAnalysis of the DatasetParameter DescriptionDataset CitationThis dataset is from ISP in china and is publicly released for researches in Edge Computing. The dataset not only contains base station location and user access time, but also records URLs, server ports and gateway IP for service/applications, which are important for edge computing researches.See more on github Francis Academic Press[PDF]
Mobile Base Station Traffic Prediction Based on Traffic
May 11, 2022 · The base station traffic has non-stationary chaotic characteristics. In addition to the traditional time series prediction method ARIMA model, scholars at home and abroad also
Mobile communication base station traffic forecast
Jul 21, 2021 · We divide the complete base station traffic data set according to the cell number to reduce the size of a single training data, which is conducive to the training of the subsequent
telecom_dataset
Oct 13, 2025 · telecom_dataset About Telecom Dataset The dataset, provided by Shanghai Telecom, contains more than 7.2 million records of
Base Station Traffic Prediction Using Wavelet Transform and
Oct 29, 2023 · The base station traffic data can be abstracted as time series with the characteristics of trend, periodicity, and randomness, which makes it suitable for predicting by
(PDF) Estimating Base Station Traffic and Throughput Using
Jan 1, 2024 · Abstract and Figures This study explores the use of machine learning algorithms to predict traffic and downlink throughput at base stations based on hourly Key Performance
Technical FAQs 4
When is the peak of traffic in a base station?
We can find that the periodic term information of the base station traffic volume data obtained by the Prophet method reaches the peak of traffic between noon and 8:30 pm. The traffic volume data is in a low valley from 3 am to 7 am.
Can gcformer predict multi-base station traffic?
Current methods often fall short in effectively harnessing long-term trends and spatial interconnections among base stations. To bridge these gaps, this paper introduces the GCformer model, a novel approach that capitalizes on both spatial relationships and temporal patterns for multi-base station traffic prediction.
How many base stations are there in the Interent dataset?
The dataset, provided by Shanghai Telecom, contains more than 7.2 million records of accessing the Interent through 3,233 base stations from 9,481 mobile phones for six months. For example, the following figure shows the distribution of base stations. Each node denotes a base station in Shanghai, China.
How to predict 5G base station traffic volume?
Based on the above definitions, the 5G base station traffic volume prediction problem can be positioned as training a model using network topology G and feature matrix X of the temporal dimension data, and then calculating the traffic volume information of the base stations for the next m time instants, as shown in Eq. 1: (1) Y = F X, G
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