Channel gain map tracking via distributed kriging

Emiliano Dall'Anese, Seung Jun Kim, Georgios B. Giannakis

Research output: Contribution to journalArticlepeer-review

90 Scopus citations


A collaborative algorithm is developed to estimate the channel gains of wireless links in a geographical area. The spatiotemporal evolution of shadow fading is characterized by judiciously extending an experimentally verified spatial-loss field model. Kriged Kalman filtering (KKF), which is a tool with widely appreciated merits in spatial statistics and geosciences, is adopted and implemented in a distributed fashion to track the time-varying shadowing field using a network of radiometers. The novel distributed KKF requires only local message passing yet achieves a global view of the radio frequency environment through consensus iterations. Numerical tests demonstrate superior tracking accuracy of the collaborative algorithm compared with its noncollaborative counterpart. Furthermore, the efficacy of the global channel gain knowledge obtained is showcased in the context of cognitive radio resource allocation.

Original languageEnglish (US)
Article number5711699
Pages (from-to)1205-1211
Number of pages7
JournalIEEE Transactions on Vehicular Technology
Issue number3
StatePublished - Mar 1 2011


  • Channel tracking
  • cognitive radio
  • distributed algorithms
  • kriging
  • shadow fading


Dive into the research topics of 'Channel gain map tracking via distributed kriging'. Together they form a unique fingerprint.

Cite this