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Master thesis: Adaptive beam measurements

Job Description

Date: Nov 8, 2019


Master Thesis @ Ericsson

 

Background

Beam Forming is used in 5G/NR and Beam Management is the mechanism that selects the active beam used for transmission between the Base Station and User Equipment (UE). Beam management is based on the continuous measurement reports from the UE on the reference signals related to the available beams.

With higher frequencies and more narrow beams for coverage enhancements, beam management is becoming increasingly important. However, it comes with a collective cost due to the frequent measurements that are needed to monitor the positions of all connected UEs.

 

Objective

Investigate methods to optimize the beam measurements, what beams to measure on, what is the most efficient way to use the measurement results and to select the ”best” beam for a UE ? Consider the periodicity /frequency of the measurements and the consumed air interface resources in downlink and uplink.

Machine learning and algorithms will be an important part of this master thesis. It is partly a continuation of previous master theses and the result of these needs to be studied.

The algorithms will be evaluated in a simulated environment and depending on the complexity and availability on a 5G test bed.

Analyze KPIs and compare with previous results, for example bit rate and latency per UE and total throughput for the cell.

 

Qualifications

  • Wireless Communications
  • Machine learning
  • Programming
  • Optimization
  • Algorithms
  • Simulation
  • Matlab

 

For more information please contact

Marcus Davidsson at marcus.davidsson@ericsson.com


Please send in your application before the 29th of November.

 

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