TY - GEN
T1 - A study of LTE network performance based on data analytics and statistical modeling
AU - Hu, Sanqing
AU - Ouyang, Ye
AU - Yao, Yu Dong
AU - Fallah, M. Hosein
AU - Lu, Wenyuan
PY - 2014
Y1 - 2014
N2 - Various simulation based approaches are developed to study wireless network performance and capacity traditionally. However, these simulation based approaches has its own limitations in supervised and unsupervised learning. Since big data techniques become more available, using big data techniques to understood the huge amount of the LTE network measurements and diagnosis data, evaluate and predict the LTE network capacity and performance becomes a very promising approach. This paper investigates the LTE network performance from the aspect of data analytics and statistical modeling. In this paper, we develop a methodology of data analytics and modeling to evaluate LTE network performance based on traffic measurements and service growth trends. A relational algorithm is developed to obtain the relationship between LTE network resources and LTE KPIs and a forecasting algorithm is developed to trend the network resource consumptions based on traffic and service growth. The numerical results show a high accuracy, robustness, and reliability of the proposed methodology.
AB - Various simulation based approaches are developed to study wireless network performance and capacity traditionally. However, these simulation based approaches has its own limitations in supervised and unsupervised learning. Since big data techniques become more available, using big data techniques to understood the huge amount of the LTE network measurements and diagnosis data, evaluate and predict the LTE network capacity and performance becomes a very promising approach. This paper investigates the LTE network performance from the aspect of data analytics and statistical modeling. In this paper, we develop a methodology of data analytics and modeling to evaluate LTE network performance based on traffic measurements and service growth trends. A relational algorithm is developed to obtain the relationship between LTE network resources and LTE KPIs and a forecasting algorithm is developed to trend the network resource consumptions based on traffic and service growth. The numerical results show a high accuracy, robustness, and reliability of the proposed methodology.
KW - Big Data Analytics
KW - LTE
KW - Network Capacity
KW - Network Performance
KW - Network Resource
KW - Statistical Modeling
UR - http://www.scopus.com/inward/record.url?scp=84904186011&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904186011&partnerID=8YFLogxK
U2 - 10.1109/WOCC.2014.6839911
DO - 10.1109/WOCC.2014.6839911
M3 - Conference contribution
AN - SCOPUS:84904186011
SN - 9781479952496
T3 - 2014 23rd Wireless and Optical Communication Conference, WOCC 2014
BT - 2014 23rd Wireless and Optical Communication Conference, WOCC 2014
T2 - 2014 23rd Wireless and Optical Communication Conference, WOCC 2014
Y2 - 9 May 2014 through 10 May 2014
ER -