5G; Indoor Localization; CSI; Machine Learning
The dataset, developed at the National Institute of Neurology and Neurosurgery in Mexico, encapsulates crucial gait biomarkers associated with neurodegenerative diseases. This invaluable compilation serves as a comprehensive resource for understanding and analyzing the distinctive gait patterns exhibited by patients grappling with neurological disorders. By delving into these intricate biomarkers, researchers gain insights into the nuanced manifestations of conditions impacting the nervous system.
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We have designed a ZYNQ SDR-based platform that utilizes real on-air 5G new radio (NR) signals to develop and test the performance of channel estimation for wireless channel estimators. On-air samples are obtained via the SDR platform to determine the unknown values of the channel response using known values at the pilot locations. We have collected extensive channel estimation data under a variety of scenarios: 1) line-of-sight (LOS), 2) LOS multipath and 3) non-LOS multipath. We have considered 2m,4m,6m test cases to simulate meter-level indoor positioning for indoor scenarios.
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