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Roohollah Amiri
Also published under:
Affiliation
Qualcomm Technologies, Inc., San Diego, USA
Topic
User Equipment,Point Cloud,Wireless Networks,3rd Generation Partnership Project,Angle Of Arrival,Artificial Neural Network,Baseline Schemes,Capacity Planning,Central Unit,Channel Impulse Response,Channel Measurements,Coverage Estimates,Digital Twin,Key Performance Indicators,Machine Learning Models,Machine Learning Solutions,Multipath Components,Neighboring Cells,Network Capacity,Network Planning,Neural Network,Potential Use Cases,Ray Tracing,Real-world Deployment,Simulation Accuracy,Simultaneous Localization And Mapping,Specular Reflection,Time-of-flight,Ultra-wideband,User Experience,2D Environment,3D Environment,5G New Radio,Active Region,Analog-to-digital Converter,Angle Measurements,Assignment Problem,Cellular Networks,Channel Model,Constant False Alarm Rate,Control Points,Deployment Scenarios,Distributed Unit,Environment Map,Fingerprinting Method,Forward-backward Algorithm,Generation Wireless Networks,Grid Search,Grid Search Method,High Load Condition,
Biography
Roohollah Amiri (Member, IEEE) received the B.Sc. and M.Sc. degrees (Hons.) in communication systems from Iran University of Science and Technology (IUST), in 2011 and 2013, respectively, and the Ph.D. degree from Boise State University, in 2020. Since then, he has been with Qualcomm Wireless Research and Development (WRD), San Diego, CA, USA. His research interests include communication systems, precise indoor positioning, joint communication and sensing, digital twins, and the application of artificial intelligence to the design and deployment of wireless networks.