2019
DOI: 10.1186/s13638-019-1392-6
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A new method for traffic forecasting in urban wireless communication network

Abstract: With the development of wireless devices and the increase of mobile users, the operator's focus has shifted from the construction of the communication network to the operation and maintenance of the network. Operators are eager to know the behavior of mobile networks and the real-time experience of users, which requires the using of historical data to accurately predict future network conditions. Big data analysis and computing which is widely adopted can be used as a solution. However, there are still some ch… Show more

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Cited by 27 publications
(15 citation statements)
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“…This scheme also takes many input data for estimations. Reference [12] also focuses on forecasting the future mobile traffic data in urban areas. They used various network oscillation factors, such as jitter, packet loss, and delay (i.e., call detail record (CDR)) for enhancing the forecast ability; in addition, they adopted LSTM architecture [7] for realizing long term forecasting.…”
Section: Related Workmentioning
confidence: 99%
“…This scheme also takes many input data for estimations. Reference [12] also focuses on forecasting the future mobile traffic data in urban areas. They used various network oscillation factors, such as jitter, packet loss, and delay (i.e., call detail record (CDR)) for enhancing the forecast ability; in addition, they adopted LSTM architecture [7] for realizing long term forecasting.…”
Section: Related Workmentioning
confidence: 99%
“…A multivariate Long Short-Term Memory (LSTM) algorithm was designed in [11] to predict the traffic networks by performing the call detail record (CDR) data analysis. The designed algorithm failed to consider the large volume of wireless data and complex data types for network prediction.…”
Section: Related Workmentioning
confidence: 99%
“…However, the performance of accurate traffic predictions was not attained. Multivariate prediction algorithms were designed in Zhang et al [4] for cellular network traffic analysis.…”
Section: Introductionmentioning
confidence: 99%