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Master Thesis: AI Powered Advanced Cell Supervision improvement at Ericsson

Karlskrona, Blekinge County, Sweden -

Full Time

Start Date

Immediate

Expiry Date

01 Feb, 26

Salary

0.0

Posted On

03 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Electrical Engineering, Computer Science, Computer Engineering, Machine Learning, Data Analysis, AI, Network Reliability, Data Storage, Historical Data Collection, Predictive Modeling, Automated Recovery, Performance Evaluation, Result Presentation

Industry

Telecommunications

Description

Join our Team About this opportunity: A sleeping cell is an unwanted condition where the cell is hanging, resulting in degraded, or no service, without alerting the operator about the ongoing situation. The operators are under pressure for better quality of service and network reliability. Sleeping cells are not possible to predict when and where a sleeping cell will occur. It is very important to quickly detect sleeping cells when they occur in the field and to perform automated recovery actions (e.g. cell restart). What you will do: In order to increase the accuracy of existing AI Powered Advanced Cell Supervision feature, there is a need to better understand if a cell is sleeping when the traffic is totally zero. There is a need to implement a solution that can accurately differentiate between an actual sleeping cell and a normal scenario (no connected users due to suburban area or during night time). The following steps are envisioned as part of the thesis work: Investigate efficient ways to collect historical data, with the requirements of low processing capacity usage, and limited data storage space. Investigate different machine learning models to predict if a real sleeping cell has been detected. Analyze results of predicted detections and evaluate performance of different machine learning models. The thesis will be concluded with a result presentation for the Ericsson research team. The skills you bring: This project aims at students in electrical engineering, computer science, computer engineering or similar. 1 student, 30 hp Ericsson AB, Kista Preferred start: Jan 2026

Responsibilities

The project involves increasing the accuracy of the AI Powered Advanced Cell Supervision feature by detecting sleeping cells. This includes investigating data collection methods, implementing machine learning models, and analyzing the results.