Master Thesis: Estimating End-User Impact of Radio Network Outages

Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · Software Engineering

In short

This Master Thesis focuses on developing and evaluating a data-driven method to estimate the impact of Radio Access Network outages on end users. The goal is to improve incident prioritization, network development, and outage monitoring, potentially utilizing machine learning techniques.

Responsibilities

Define measurable indicators of user impact, including loss of service, reconnection to neighboring cells, and degraded performance.
Identify neighboring cells that absorb traffic from an affected cell using mobility statistics, handover data, and outage measurements.
Estimate the impact on users connected to the affected cell as well as users in neighboring cells affected by increased traffic or congestion.
Use a network simulator with known ground truth and realistic outage scenarios to validate the proposed method.
Analyse the results and suggest practical improvements to existing methods for monitoring and observing network outages.

Requirements

Studies in Engineering Physics, Applied Mathematics, Data Science, Computer Science, or a similar field.
A solid background in statistics and time-series analysis.
An analytical and structured approach to problem-solving.
An interest in data-driven methods and machine learning.
Ability to work independently as well as collaboratively.

Desired Qualifications

Previous knowledge of Radio Access Networks is beneficial but not required, as relevant knowledge will be introduced during the thesis.

Benefits

Outstanding opportunity to use your skills and imagination to push the boundaries of what's possible.
Build solutions never seen before to some of the world's toughest problems.
Be challenged, but not alone.
Join a team of diverse innovators.
Opportunity to craft what comes next.

Skills

StatisticsTime-series analysisMachine learningData scienceComputer scienceEngineering PhysicsApplied Mathematics

#radio access networks#network outages#end-user impact#machine learning#data-driven methods#incident prioritization#network development#network monitoring#Sweden#Linköping#master thesis

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