Spectrum cartography using adaptive radial basis functions: Experimental validation
Idsøe, Henning; Hamid, Mohamed; Jordbru, Thomas; Cenkeramaddi, Linga Reddy; Beferull-Lozano, Baltasar
Journal article, Peer reviewed
Accepted version
Permanent lenke
http://hdl.handle.net/11250/2493359Utgivelsesdato
2017Metadata
Vis full innførselSamlinger
Originalversjon
Paper presented at the 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). 10.1109/SPAWC.2017.8227752Sammendrag
In this paper, we experimentally validate the functionality of a developed algorithm for spectrum cartography using adaptive Gaussian radial basis functions (RBF). The RBF are strategically centered around representative centroid locations in a machine learning context. We assume no prior knowledge about neither the power spectral densities (PSD) of the transmitters nor their locations. Instead, the received signal power at each location is estimated as a linear combination of different RBFs. The weights of the RBFs, their Gaussian decaying parameters and locations are jointly optimized using expectation maximization with a least squares loss function and a quadratic regularizer. The performance of adaptive RBFs based spectrum cartography is shown through measurements using a universal software radio peripheral, a customized node and LabView framework. The obtained results verify the ability of adaptive RBF to construct spectrum maps with an acceptable performance measured by normalized mean square error (NMSE).