Analytical Approximation-Based Machine Learning Methods for User Positioning in Distributed Massive MIMO

Analytical Approximation-Based Machine Learning Methods for User Positioning in Distributed Massive MIMO

We propose a machine learning approach, based on analytical inference in Gaussian process regression (GP), to locate users from their uplink received signal strength (RSS) data in a distributed massive multiple-input-multiple-output setup. The training RSS data is considered noise-free, while the te...

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Bibliographic Details
Main Authors: K. N. R. Surya Vara Prasad, Ekram Hossain, Vijay K. Bhargava, Shankhanaad Mallick
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Machine learning
Gaussian process regression
massive MIMO
user positioning
Online Access:https://ieeexplore.ieee.org/document/8290939/

Internet

https://ieeexplore.ieee.org/document/8290939/

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