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Location-Free Spectrum Cartography.
- Source :
-
IEEE Transactions on Signal Processing . 8/1/2019, Vol. 67 Issue 15, p4013-4026. 14p. - Publication Year :
- 2019
-
Abstract
- Spectrum cartography constructs maps of metrics such as channel gain or received signal power across a geographic area of interest using spatially distributed sensor measurements. Applications of these maps include network planning, interference coordination, power control, localization, and cognitive radios to name a few. Since existing spectrum cartography techniques require accurate estimates of the sensor locations, their performance is drastically impaired by multipath affecting the positioning pilot signals. This phenomenon occurs especially in indoor or dense urban scenarios. To overcome such a limitation, this paper introduces a novel paradigm for spectrum cartography, where estimation of spectral maps relies on features of these positioning signals rather than on location estimates. Specific learning algorithms are built on this approach and offer a markedly improved estimation performance than those of the existing approaches relying on localization, as demonstrated by simulation studies in indoor scenarios. [ABSTRACT FROM AUTHOR]
- Subjects :
- *CARTOGRAPHY
*DISTRIBUTED sensors
*MACHINE learning
*COGNITIVE radio
Subjects
Details
- Language :
- English
- ISSN :
- 1053587X
- Volume :
- 67
- Issue :
- 15
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Signal Processing
- Publication Type :
- Academic Journal
- Accession number :
- 138231950
- Full Text :
- https://doi.org/10.1109/TSP.2019.2923151