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Hub for Good




Ericsson partners

Hatem Abou-Zeid, Dimple Thomas

Research project

We have observability into the spatial distribution of users and beam energy at any advanced antenna system site. There is a great opportunity to utilize this information to tune and optimize the AAS site and radio network 

Wireless cellular networks have rapidly been developing during the last three decades. The commercial wireless industry has recently started deploying fifth generation (5G) technology worldwide. 5G networks hold great potential to enable ubiquitous low-latency and high-speed communication connections. One prominent feature of 5G networks is the use of advanced antenna systems (AAS) comprising a large number of antenna elements that can be used in varied beamforming schemes. 

The focus of this project is to combine a theoretically driven approach alongside analysis of field collected uplink sounding reference signal data (SRS) transmitted by several user terminals (UEs)

The goal in this project is to perform research and provide solutions to the following challenges: 

a) Reuse existing sounding reference signal channel estimation datasets to reconstruct channel conditions experienced by different users located within the cell/sector 

b) Enhance existing tools to provide real-time channel reconstruction of said datasets 

       a. Use machine learning and AI to predict channel conditions, and devise smarter, efficient beamforming schemes based on advanced channel learning 

       b. Use augmented/virtual reality to visualize channel conditions in real-time

       c. Overlay channel information using real-time mapping software 

       d. Enhance channel simulators based on real-time measurements

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Carleton University
Human Computer Interaction Building
1125 Colonel By Drive
Ottawa, ON, K1S 5B6
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