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Projeto de investigação
Measuring Mobile Broadband Networks in Europe
Financiador
Autores
Publicações
Affordable LTE network benchmarking based on transport fleets
Publication . Dionísio, Rogério Pais; Marques, Paulo; Marques, Hugo; Alves, Tiago Ferreira; Pereira, Luis Miguel Cardoso; Silva, Fernando; Ribeiro, Jorge Miguel Afonso
To gain competitive advantage in today’s mobile
market, cellular network testing, monitoring and improving
customer experience is crucial. Today independent benchmarking
companies are hired by mobile operators to run drive tests in
a certain geographical areas. The high cost for running these
tests results in a low frequency of execution, typically this
benchmarking is executed no more than two or three times
per year, which is not sufficient to follow the dynamics of
an LTE network in a dense urban area. The majority of the
drive testing costs come from the car, driver, and the in-car
technician. Another approach is to take advantage of existing
transportation companies to carry on network benchmarking
services to Mobile Network Operators. Unattended measurement
nodes can be deployed in existing transportation fleets without
the need for dedicated field personnel, reducing the cost of testing
up to 70%. This demo uses nodes placed in buses, available in
several cities in Europe, to create and validate an automatic
LTE network benchmark. The tool allows an easy comparative
analyses of mobile network quality of Service and quality of
experience parameters based on the operators raw data.
Data analytics for forecasting cell congestion on LTE networks
Publication . Torres, Pedro; Marques, Paulo; Marques, Hugo; Dionísio, Rogério Pais; Alves, Tiago Ferreira; Pereira, Luis Miguel Cardoso; Ribeiro, Jorge Miguel Afonso
This paper presents a methodology for forecasting the average downlink throughput for an LTE cell by using real measurement data collected by multiple LTE probes. The approach uses data analytics techniques, namely forecasting algorithms to anticipate cell congestion events which can then be used by Self-Organizing Network (SON) strategies for triggering network re-configurations, such as shifting coverage and capacity to areas where they are most needed, before subscribers have been impacted by dropped calls or reduced data speeds. The presented implementation results show the prediction of network behaviour is possible with a high level of accuracy, effectively allowing SON strategies to be enforced in time.
Unidades organizacionais
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Financiadores
Entidade financiadora
European Commission
Programa de financiamento
H2020
Número da atribuição
644399