A Distributed Massive MIMO Channel Sounder for “Big CSI Data”-driven Machine Learning

Inhalt:
A distributed massive multiple-input multipleoutput (MIMO) channel sounder for acquiring large channel state information (CSI) datasets, dubbed Distributed Channel Sounder by University of Stuttgart (DICHASUS), is presented. The measured data has potential applications in the study of various machine learning algorithms for user localization, Joint Communication and Sensing (JCAS), channel charting, enabling massive MIMO in frequency division duplex (FDD) operation, and many others. The proposed channel sounder architecture is distinct from similar previous designs in that each individual single-antenna receiver is completely autonomous, enabling arbitrary, spatially distributed antenna deployments, and offering virtually unlimited scalability in the number of antennas. Optionally, extracted channel coefficient vectors can be tagged with ground truth position data, obtained either through a global navigation satellite system (GNSS) receiver (for outdoor operation) or through various indoor positioning techniques.