Intelligent Test Traffic Generator for Telecommunications Networks

Ericsson Hungary needs a Test Traffic Generator for telecommunications networks to test data analytics applications. The generator should solve the time-consuming problem of anonymising personal data for testing purposes, replacing it with fake, but realistic generated data. The EIT Digital Doctoral School has one open position for an industrial doctorate in Budapest. A six-month stay at one of the best European research institutions in this field is part of the programme.


Data processing and analytics applications should behave robustly, both in case of everyday use-case scenarios and in yet unseen or unexpected situations. To deliver robust solutions, developers routinely test their products in simulated scenarios. However, input data to analytics applications often contains personal information, limiting its availability to test engineers or data scientists. And even when they are available, datasets need to be anonymised, resulting in a slow, non-scalable process. “We often lack proper data for testing due to the need for anonymity and because operators do not want to disclose real data, so this approach might solve an important point”, says Henrik Abramowicz, Action Line Digital Infrastructure EIT Digital to underline the importance of this industrial doctorate.


The Test Generator should address a pain of test engineers and developers of telecommunications applications: the need to test their systems with realistic data. Also, the built-in adaptability of the generator should be future proof and applicable to networks of evolving technologies. One important use-case application is in the domain of 5G networks.

This student undertaking this industrial doctorate will investigate the data processing landscape and application use-cases of Ericsson. He or she will then implement appropriate data mining and machine learning techniques and develop and implement state-of-the-art techniques for synthetic data generation. Then, the results will be integrated into a single, modular framework. Finally, the solution will be tested and refined.

Expected outcome

The result is a novel Intelligent Test Traffic Generator that can learn the characteristics of a given real database with limited access and generating synthetic but realistic data, like the input database. The data are generated for evaluating and tuning data analytics applications or performance testing of developed software solutions. The Test Traffic Generator will be easily adaptable to requirements and needs of other industrial partners and, thus, it might be extended to a possible commercial product.


The doctoral student involved in this programme will share its time between the Co-Location Centre of the EIT Digital Budapest Node, the premises of Ericsson Hungary, and the Eötvös Loránd University. A 6-month mobility to one of the best known European research groups in this field will be also part of the program.


  • Industrial partner: Ericsson Hungary Ltd.
  • Academic/research partner: Eötvös Loránd University
  • Number of available PhD positions: 1
  • Duration: 4 years
  • This PhD will be funded by EIT Digital, Eötvös Loránd University and Ericsson Hungary Ltd.


If you are interested in applying for this position, please send an e-mail to the EIT Digital DTC lead, including a CV, a motivation letter, and documents showing your academic track records.

Please apply before November 1, 2017.

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