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Master Thesis: Making use of IoT

Job Description

Date: Nov 8, 2019

Ericsson Research
Ericsson Research develops new communication solutions and standards. The organization has responsibility to provide Ericsson with world-class system concepts, technology innovations, and methodologies. The rapidly increasing demands for mobile broadband access in combination with needs for new technology and solutions for the digitalization of industries and societies creates challenging and exciting opportunities for our organization. Building on our experience from real network operations, profound knowledge about existing standards, and forward-looking research, we invent and master advanced concepts and solutions that shape today and tomorrow´s mobile radio communication.


In the scope of 5G there is a type of IoT that is based on fairly simple hardware and with requirements to be able to work for a long time without having to charge the battery, while keeping costs as low as possible. In the scenarios foreseen such devices will be deployed in large amounts in various locations. Since coverage is good such devices can, e.g., be deployed in shallow tunnels in cities (such as cut-and-cover subway tunnels) or basements in buildings.
The value of a separate connection is small. With very many connections the sum of all connections naturally results in a larger value; value is a sum of all the separate measurements. However, by finding a pattern in the data that would help draw conclusions and obtain a deeper insight, it could be possible to further increase the value of the measurements. In other words, even though there is some value in having such sensors provide simple readings and humidity, temperature, or motion sensors, there may be more value by using the sensors in some more elaborate way. By using the information from the devices it should be able to extract more value than just the set of measurements.

Thesis Description

For this thesis we want to find ways to extract information from measurements and apply some means to increase the “value” of the measurements.  The thesis can take different routes depending on the competence and interests of the thesis worker. One example is to look at the data and all that there is. Remember that the data is not only the actual measurement, but also the position of the device, the time, current radio conditions, outdoor weather, etc. Will using all possible information help improve output from sensors? Perhaps an analysis of the data can help in setting up measurements campaigns.
Another possible direction is to use the hardware of the devices to process data. Each separate device has limited processing performance. However, there are very many devices. So if the processing can be split among the devices there is a lot more processing power. Perhaps the devices can be used to train a model for interpreting the data, thus making it possible to provide insights to some cloud service that is impossible to attain by the cloud itself. One simple example is that the device can determine to not send measurements at all.
The thesis will be concluded with a result presentation for the Ericsson Research team.


  • The successful applicant will be a self-motivated MSc student or equivalent with an interest in machine learning, algorithm development and testing
  • The work is research oriented, so ability to learn quickly, work independently and identify problems and solutions is necessary
  • You should be an MSc student, preferably in engineering physics, electrical engineering, computer science or similar
  • Courses in wireless communication theory and signal processing as well as experiences of communication systems and internet protocols are considered valuable merits.

Extent: 1 student, 30hp
Work location: Luleå
Preferred Starting Date: Q1 2020, please enclose a transcript in your application and state when you can start.
Last Day to Apply: 24th of November
Contact: Mats Nordberg, +46703008001, or Agnes Westerberg,



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Primary country and city: Sweden (SE) || || Luleå || Stud&YP

Req ID: 304600