Spectrum Cartography
3 papers with code • 0 benchmarks • 0 datasets
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Latest papers with no code
Radio Map Estimation: A Data-Driven Approach to Spectrum Cartography
Radio maps characterize quantities of interest in radio communication environments, such as the received signal strength and channel attenuation, at every point of a geographical region.
Spectrum Cartography via Coupled Block-Term Tensor Decomposition
Spectrum cartography aims at estimating power propagation patterns over a geographical region across multiple frequency bands (i. e., a radio map)---from limited samples taken sparsely over the region.
Data-Driven Spectrum Cartography via Deep Completion Autoencoders
The resulting algorithms can therefore construct a spectrum map from a significantly smaller number of measurements than existing schemes since the spatial structure of shadowing and other phenomena is previously learned from maps in other environments.
Functional Nonlinear Sparse Models
Even if they are, recovering sparse solutions using convex relaxations requires assumptions that may be hard to meet in practice.
Decentralized learning for wireless communications and networking
This chapter deals with decentralized learning algorithms for in-network processing of graph-valued data.
