Machine Learning Methods for RSS-Based User Positioning in Distributed Massive MIMO.
IEEE Transactions on Wireless Communications(2018)
Abstract
We propose a supervised machine learning (ML) approach based on Gaussian process (GP) regression to position users in a distributed massive multiple-input multiple-output (DM-MIMO) system from their uplink received signal strength (RSS). The proposed approach serves as a proof-of-concept that we can localize users by training an ML model with noise-free RSS and using the trained model to estimate ...
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Key words
MIMO communication,Machine learning,Machine learning,Wireless communication,Shadow mapping,Noise measurement,Uplink,Gaussian processes,Cramer-Rao bounds
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